Marine Vehicle Spectrum Signature Detection Based On An Adaptive CFAR and Multi-Frame Fusion Algorithms

Size: px
Start display at page:

Download "Marine Vehicle Spectrum Signature Detection Based On An Adaptive CFAR and Multi-Frame Fusion Algorithms"

Transcription

1 Daha Cheng Marne Vehcle Spectrum Sgnature Detecton Baed On An Adaptve CFAR and Mult-Frame Fuon Algorthm Daha Cheng School of Electrc and Automatc Engneerng Changhu Inttute of Technology Changhu Jangu Chna. 55 Abtract Detectng marne vehcle pectrum gnature from hydrophone at low fale alarm rate and hgh detecton rate n an envronment of varou nterference a very dffcult problem. To overcome th problem an obervaton pace created by amplng and dvdng nput analog acoutc gnal nto dgtal gnal n multple frame and each frame tranformed nto the frequency doman; then an Adaptve Contant Fale Alarm Rate ACFAR and ot Detecton Fuon algorthm have been propoed for an effectve automatc detecton of marne vehcle generated acoutc gnal pectrum gnature. The propoed algorthm have been teted on everal real acoutc gnal. The tattcal analy and epermental reult howed that the propoed algorthm ha ept a very low fale alarm rate and etremely hgh detecton rate. Keyword: Target Spectrum Sgnature Detecton Mult-frame Acoutc Sgnal roceng Tme- Frequency Doman Adaptve Contant Fale Alarm Rate ACFAR.. ITRODUCTIO For the urgent need of Chna' natonal defene and ocean defene n the coatal area the deployment of deep-ea underwater onar detecton ytem networ wll greatly enhance the ablty of montorng and controllng of varou nd of hp ncludng unmanned hp and ubmarne actvte n Chna Sea. The etablhment of onar detecton networ ytem can weaen the combat capablty of foregn underwater hp and ubmarne n many way whch the foundaton of the concept of Area battle. Moreover f the onar real-tme detecton ytem can be deployed to the Yellow Sea South Chna Sea and Eat Chna ea bottom and can be lned a a networ the unepected marne vehcle uch a ubmarne can only tay outde of the networ coverage. Th wll greatly weaen the foregn troop n the conflct n the coatal area near man land Chna. Wth the ncreae of unauthorzed arrval drug muggler llegal fhng and a range of other border threat the border protecton become more and more mportant to the nternatonal communty. An alarmng ytem whch can detect and report the etence of alen marne vehcle becomng an urgent ta for the authorty. The author targetng the applcaton on thee apect by uccefully developed a very effectve acoutc gnal detecton algorthm whch can be ued for detecton and montorng of llegal actvte on the wde range of coatlne by detectng any unepected marne vehcle by mean acoutc technque [-[7. Th paper focued on the theoretcal algorthm development and epermental reearch of automatc detecton of acoutc gnal epecally for boat generated gnal by hydrophone [8- [. In th paper an obervaton pace created by dvdng nput acoutc gnal nto multple frame and each frame ampled and tranformed nto the frequency doman. The multple frame gnal proceng algorthm propoed n th paper for the purpoe of ncreang the probablty of fnal detecton. Some ample of the obervaton pace are hown n Fg. n Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 9

2 Daha Cheng whch the horzontal a frequency n z and vertcal tme n econd or number of frame. We can alo ee that there are not only the vertcal frequency trp that are generated by marne vehcle but alo ome curved trp that are caued by mult-path effect due to hallow water envronment. FIGURE : Sample of Obervaton Space Tme and frequency pace. The concept of Contant Fale Alarm Rate and t applcaton had been ued n radar ytem for a long tme [5-[5. But there no approprate CFAR algorthm wa propoed n onar ytem epecally for the practcal applcaton. In th paper an Adaptve Medan Contant Fale Alarm Rate MCFAR algorthm n tme-frequency doman ha been propoed for automatc detecton of boat generated acoutc gnal n each frame n whch a low contant fale alarm rate ept wth relatvely hgh detecton rate frt. Then a pot detecton fuon algorthm wth tme or number of frame propoed to ncreae probablty of fnal detecton and mae the whole detecton more robut. The propoed algorthm have been teted on real acoutc gnal receved and recorded from hydrophone whch were generated by real marne vehcle called Kmbla Ferry aad aad Reef heron Reef heron and Kuala Lumpur.. OTIMUM DETECTIO STRUCTURE UDER TE EYMA-EARSO CRITERIO. Optmum detecton tructure under the eyman-earon crteron for a ngle bn n a gven frame and a frequency bn The acoutc gnal detecton and mult-frame fuon algorthm propoed n th paper are tructured baed on the eyman-earon crteron [6-[3. Th crteron utable for target detecton applcaton ether n onar or radar ytem. The obervaton pace of the Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8

3 The th Tme frame Vector Tme umber of Frame Daha Cheng detector hown n Fg. n whch horzontal drecton repreent frequency number of frequency bn and vertcal drecton repreent tme number of frame. Frequency umber of Frequency Bn M L L M M... M L L The th Obervaton Vector- X OV X TF FIGURE : Obervaton Space for The Acoutc Sgnal eyman-earon Detector. The followng analy baed on the gnal n the frequency doman [3-[3 n th frame and th frequency bn. The hypothe tet aume: : n : n. Where n the noe ample n th frame and th frequency bn the gnal ample n th frame and th frequency bn n whch... M the nde of frame n the propoed algorthm. We aume that the noe n all frequency bn are ndependent and ha the ame Gauan probablty dtrbuton wth the mean and varance.e. n. The gnal S n all dfferent frequency bn are non-random contant. Thee aumpton are qute true for the hort perod of obervaton of 5 to econd. In hypothe we aume that the receved dgtal gnal n th frame and th frequency bn only contan noe. In hypothe we aume that the receved dgtal equence n th frame and th frequency bn contan gnal and noe. Thu the probablty dtrbuton functon pdf of equaton. under the hypothe hown n p ep[ Smlarly the probablty dtrbuton functon pdf of equaton 3. under the hypothe hown n Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8

4 Daha Cheng p S ep[ 3 In order to eep a contant fale alarm rate and mamze the gnal detecton probablty n each frequency bn a Medan CFAR algorthm propoed n the paper whch wll be decrbed n medan ecton. In whch a floatng threhold the medan value of the frequency bn that are covered by a ldng wndow.e. medan Medan The Medan flter ze n whch 3. We aume the medan wndow ze bg enough to eclude the etent gnal n th frame and medan th frequency bn o the an accurate etmate of the neghborhood noe. So the probablty dtrbuton functon pdf of the medan n dfferent frame and frequency bn alo ha a Gauan probablty dtrbuton wth the mean and the varance.e. p medan medan ep[ 5 ence the hypothe after Medan CFAR operaton become : : medan medan n n n medan medan n. 6 Baed on the law- the lnear combnaton of ndependent Gauan random varable tll a Gauan random varable [8. We alo now that under both and hypothe obey a Gauan dtrbuton. So under the hypothe the mean of medan E{ } E{ n n } E{ n } E{ n hown n equaton 7. medan } 7 The varance of calculated and hown n equaton 8. E{ n 8 E{ E{ n E{ } } E{ n } } E{ n E{ n medan n medan } n E{ n E{ n medan medan } E{ n } } }} E{ n medan E{ n medan } } Snce n and medan n are ndependent medan medan E { n E{ n } n E{ n }} 9 The equaton 8 become E{ n E{ n } } E{ n medan E{ n medan } } Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8

5 Daha Cheng Thu the probablty dtrbuton of under hown n equaton. p ep[ Smlarly under the hypothe The mean hown n equaton. medan E { } E{ n n } The varance of calculated and hown n equaton 3. E{ E{. n E{ n medan } } } 3 So the probablty dtrbuton of under hypothe hown n equaton. p ep[ The pcture of p and p are hown n Fg. 3. FIGURE 3: robablty dtrbuton of p and p after Medan CFAR operaton Snce n the pave onar applcaton we do not now the pror probablte and but we now the probablty dtrbuton pdf of gnal and noe. In th cae eyman- earon appled n whch under the pecfed contant fale alarm rate the probablty of detecton D mamzed. In Fg. 3 the probablty of fale alarm detecton of the gven bn - fa the area of the fa Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 3

6 Daha Cheng Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 functon p above the detecton threhold -.e. fa d d p ep[ 5 The probablty of the detecton of the gven bn -. D the area of the functon p above the detecton threhold -.e. D d d p ep[ 6 Baed on the eyman-earon crteron the goal of eepng the fale alarm rate fa n an acceptable level and mamzng the detecton rate. D can be acheved by ung a lelhood rate tet LRT [6. The lelhood rate tet of the above hypothe can be repreented a: p p p p : : 7 Replacng p and p wth equaton and we can obtan the lelhood rate whch hown n equaton 8. } ep{ } ep{ p p 8 Thu the lelhood rate tet hown n equaton 7 can be mplfed by replacng wth equaton 8 ln [ : ln [ : 9 Then the optmum threhold can be repreented n the followng equaton: ln [

7 Daha Cheng If we aume that the gnal trength and noe or clutter level are contant n all bn n dfferent frame durng the obervaton perod Th qute true for the 5 to econd obervaton tme. the optmum threhold alo contant for bn durng the ame obervaton perod.e. [ ln ln We can ee that the optmum detecton threhold a functon of the gnal trength and the noe level.. Detector erformance Meaurement After ot-detecton Fuon The pot-detecton fuon algorthm after ngle frame detecton decrbed n Secton 3 n equaton 3 to 37. The output of ngle frame detecton can be decrbed n the followng vector Y [ y y y y L Where the output of th bn repreented n equaton 3. M y y 3 Where the y hown n equaton. y medan otherwe In order to calculate the performance of our detector we need to calculate the followng probablte. Snce y can be treated a a bnary random varable the probablty of y hown n equaton 5. [ y medan [ 5 fa D Replace equaton 5 and 6 n equaton 5 we obtan [ y 6 d d ep[ ep[ Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 5

8 Daha Cheng Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 6 Smlarly we can obtan d d y ep[ ep[ [ 7 So the probablty of = M bn uccefully detected n M frame n th frequency bn calculated n the followng equaton. M M M M d d d d M M y y C y y } ep[ ep[ {. } ep[ ep[ {!!! } [ { } [ { [ [ 8 Thu the probablty of detecton n th bn after pot-detecton fuon can be calculated a follow. M D d d d d M M y y } ep[ ep[ {. } ep[ ep[ {!!! [ [ 9 Where the fnal detecton threhold and t value n the range of to M. The fale alarm rate n the detecton of n th bn after pot-detecton fuon can be gven n equaton 3. M D fa d d d d M M } ep[ ep[ {. } ep[ ep[ {!!! 3 Baed on equaton 9 and 3 we can ee that both probablte of detecton and fale alarm rate of our detector after pot-detecton fuon are the functon of gnal trength noe power.e. SR probablty threhold M / fuon frame number M and potental functon of Medan CFAR wndow length.

9 Daha Cheng 3. MULTI-FRAME ACOUSTIC SIGAL ROCESSIG AD DETECTIO ALGORITM I TE FREQUECY DOMAI A mult-frame acoutc gnal proceng and detecton algorthm n the frequency doman are propoed n th paper a ummarzed n Fg.. FIGURE : Mult-Frame Acoutc Sgnal roceng and Detecton Algorthm. Acoutc gnal from hydrophone are converted nto dgtal gnal baed on the yqut Samplng Theorem Crteron [33-[38 mpong a amplng rate larger than twce the mamum gnal frequency. In our eperment we ued a amplng rate of 8 z o the mamum frequency we are ntereted z. Then the dgtal gnal converted from analog nput gnal dvded nto frame. Each frame lat T econd and n our eperment the T wa choen a.5 econd wth the amplng rate 8 z o the data proceng perod n dgtal format =. In order to detect acoutc gnal typcally boat generated gnal the dgtal gnal need to be tranformed nto the frequency doman frame by frame. In our eperment the dgtal gnal are tranformed nto the frequency doman by ung FFT whch the fatet and mot effectve algorthm for Dgtal Fourer Tranform DFT. Snce the data proceng perod n dgtal format n our eperment we chooe the ame length a FFT length whch alo pont. Some frame pre-proceng n the frequency doman neceary before we tart detectng gnal frequence whch nclude DC removal and pectrum frame vector normalzaton. DC removal requred becaue all acoutc gnal have a DC component ometme very trong Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 7

10 Daha Cheng whch not part of the gnal generated by a target boat but can affect our target frequency component detecton reult. The DC component removed alo becaue t doe not carry any ueful nformaton. In order to deal wth varou nput gnal trength and mae the whole automatc detecton robut ngle frame pectrum magntude normalzaton performed n the frequency doman. At th tage each element n the frame vector dvded by the magntude of the vector geometrc length. After normalzaton a magntude amplfcaton of db tme ued to gve the gnal a reaonable dynamc value range. The ngle frame pectrum vector normalzed by t vector length whch decrbed a follow X XTF norm f f XTF In whch frame nde and dynamc range n our eperment T L L 3 f a calng factor that eep the whole vector n a reaonable f choen a db. Then an adaptve medan CFAR algorthm propoed to calculate the Contant Fale Alarm Rate threhold n a ngle frame n whch the threhold for each frequency bn the medan value of t ldng wndow. After that the nput gnal pectrum compared wth the CFAR threhold and f the dfference bgger than a contant threhold t reported a target frequency otherwe t treated a bacground noe. The called entvty of our detecton ytem. The bgger the the le entve our detecton ytem. Snce the CFAR threhold n each bn calculated baed on t neghborhood noe t wll eep our automatc detecton ytem at low and contant fale alarm rate. The Adaptve Medan Contant Fale Alarm Rate Adaptve Medan CFAR threhold vector medan norm X calculated by pang X nto a Medan flter Where the the frame nde and the properte and ze of th flter wll be dcued n the net ecton. whch medan medan medan medan medan [ L T X 3 Where the frame nde and L the frequency bn nde and each threhold element medan norm norm norm norm norm Medan 33 In whch the Medan flter ze and 3. And the ngle frame detecton reult a bnary vector whch baed on the comparon of the vector hown n equaton 3 Y y y y L T norm X and medan X and the output 3 Where the the frame nde the the frequency bn nde and y L ngle frame detecton output whch y norm otherwe threhold 35 Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 8

11 Daha Cheng where a contant threhold and the the more entve our detector. called entvty n our eperment. The maller Baed on the eyman-earon crteron the mot mportant apect n target frequency component detecton to ncreae the probablty of detecton. Accordngly the fuon of ngle frame detecton reult over tme.e. over a number of frame wa ued to ncreae the fnal detecton probablty. A typcal value of fuon tme for onar buoy acqured gnal about 5 econd whch correpond to about 5 frame n our tetng ytem. The Integrated Detecton vector p [ p p p L M M Y [ y y... y L 36 The p vector a decrpton of the frequency or tme of ngle frame detecton of each frequency bn and fnal detecton baed on the dtrbuton functon. In order to mae the performance of the detecton ytem more robut epecally for wea gnal the Integrated Detecton Vector normalzed by t geometrc magntude p / p and amplfed by a calng factor p db n whch the fnal detecton wll be more robut and relable.. MEDIA COSTAT FALSE ALARM RATE DETECTIO ALGORITM I TE FREQUECY DOMAI Baed on the eyman-eron crteron n order to reduce fale alarm rate durng the target gnal detecton an adaptve medan CFAR algorthm propoed n th paper n whch acoutc target gnal are detected wth a low fale alarm and relatve hgh detecton rate n the frequency doman. The frt tep to tranform nput acoutc gnal nto the frequency doman by ung FFT then an optmze algorthm wll be ued to detect target generated frequency component. The bac dea of the propoed algorthm that for each frequency bn ue dfferent adaptve CFAR Contant Fale Alarm Rate threhold rather than a ngle contant threhold whch often the cae n acoutc ytem [-[33. The threhold of each frequency bn baed on t urroundng bacground noe. The hgher the bacground noe the hgher the threhold et. To the bet of our nowledge whle th dea often ued n radar ytem to obtan lower fale alarm rate wth relatvely hgher target detecton rate t appled here for the frt tme to onar-generated acoutc gnal epecally for the propoed Medan CFAR algorthm. Moreover the Medan CFAR algorthm ue a Medan Flter Wndow centered around each frequency bn to calculate the threhold value for the nput gnal. Snce the medan flter good at removng hgh frequency pe noe t a very good way to calculate threhold vector wthout beng affected by etent gnal. The relatonhp between nput gnal pectrum vector and t threhold vector ame a pang an nput gnal pectrum nto a Medan Flter n frequency doman and output gnal our threhold vector whch hown n Fgure 5. FIGURE 5: Relatonhp Among Input Acoutc Sgnal It Spectrum And Threhold. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 9

12 Daha Cheng The Adaptve Medan CFAR algorthm uperor over the Average CFAR algorthm nce n the Average CFAR algorthm every pel n the averagng wndow wll affect the threhold epecally when the gnal or a noe pe trong. The maor advantage of the Medan flter t ablty to remove nterference uch a a trong gnal or noe pe wthout affectng the harpne of edge retanng harp edge after flterng. Converely wth an averagng LF low pa flter whch equvalent to the Average CFAR algorthm harp edge wll be blurred after flterng. The trong gnal a maor nterference affectng t accuracy when calculatng the threhold. Further evdence of the uperorty of the medan flter wth repect to average flter for the decrpton of the bacground proce can be found n [6-[3. The ze of Medan Flter wndow an odd number whch can be 357. The prncple of the Medan CFAR algorthm llutrated n Fg. 6 by ung a wndow ze of 5 whch ha been proved to be approprate n our epermental applcaton. Input Sngle Frame Sgnal Spectrum Vector norm norm norm norm norm norm norm norm L norm L Correpondng CFAR Threhold Vector Medan CFAR Flter medan medan medan medan medan medan medan medan medan L L FIGURE 6: Medan CFAR Algorthm rncple. The threhold vector calculated by pang a ldng wndow through the nput frequency vector. Each threhold the medan value of the frequency bn that are covered by ldng wndow. A hown n Fg. 6 the threhold of the th frame and th frequency bn wth the propoed Medan CFAR wndow ze of + hown n equaton 37. medan norm norm norm norm norm Medan 37 Where M nde of frame L the frequency bn number L the ngle frame vector length n frequency doman and alo the FFT length and the wndow ze. And n order to deal wth edge pel tuaton both nput gnal pectrum vector and threhold vector are treated a wrapped perod gnal. The propoed adaptve CFAR Contant Fale Alarm Rate algorthm ued to detect target generated frequency component wth relatvely hgh detecton rate whle mantanng a low and contant fale alarm rate. The ze of the Medan wndow ha to be an odd number whch ha an effect on the output threhold gnal. In the epermentaton 3 5 and 7 have been choen. The mpact of the wndow ze hown n Fgure where t can be een that the larger the wndow ze the lower frequency component et on the output threhold mage. 5. EXERIMETAL RESULTS WIT TE ROOSED MEDIA CFAR AD MULTI-FRAME FUSIO ALGORITM I TE FREQUECY DOMAI The tet gnal are provded by Soncom TY LTD whch are from C-Buoy/Off-Buoy roceor Sea Tral at Low Ilet on 7 June n Autrala. Thee real onar gnal are orgnal Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 3

13 Daha Cheng ampled at amplng rate of z and down ampled nto 5 z n order to meet our target detecton epermental purpoe. Thee acoutc gnal generated by marne vehcle are called Kmbla Ferry aad aad Reef heron Reef heron and Kuala Lumpur for the followng reference. 5. Medan CFAR Algorthm Sngle Frame Acoutc Sgnal Detecton Tet The propoed Medan CFAR algorthm ha been teted on ngle frame real acoutc gnal whch hown n Fg. 7a. We can ee that there a very trong gnal component located about 6 z the trength about 3 db. and there are alo ome harmonc frequency component around z but are much maller than the man one. a Kmbla boat ngle frame gnal pectrum b Kmbla gnal pectrum threhold obtaned by applyng a Medan CFAR Wndow Sze of 3 c Kmbla gnal pectrum threhold obtaned by applyng a Medan CFAR Wndow Sze of 5 d Kmbla gnal pectrum threhold obtaned by applyng a Medan CFAR wndow ze of 7 FIGURE 7: 'Kmbla' real acoutc gnal ngle frame pectrum and t Medan CFAR threhold. Fg. 7 b c and d how u the threhold gnal pectrum vector obtaned by applyng a Medan CFAR wndow wth the wndow ze of 3 5 and 7 repectvely. We can ee that the bgger the wndow ze the moother the threhold gnal vector le hgh frequency component. Although there are ome pe n the threhold mage uch pe le than or 5 db are much maller than gnal about 3 db. Overall we can alo ee that the threhold n all three cae are all below.5 db n ther trength whch are much maller than the man gnal trength Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 3

14 Daha Cheng of 3 db. The eample reult of ngle frame acoutc gnal hown n Fg. 7 detecton by ung the propoed Medan CFAR Algorthm are hown n Fg. 8. a Detected target frequency wth Medan CFAR algorthm wndow ze of 3 and default entvty. b Detected target frequency wth Medan CFAR algorthm wndow ze of 5 and default entvty. c Detected target frequency wth Medan CFAR algorthm wndow ze of 7 and default entvty. FIGURE 8: 'mbla' real acoutc gnal ngle frame detecton reult by ung Medan CFAR threhold. Fg. 8 how u the detecton reult of Kmbla ngle frame gnal by ung the propoed Medan CFAR algorthm and we can ee both the man gnal frequency component at about 6 z and t harmonc component around z are correctly detected by ung three dfferent Medan CFAR wndow ze under the condton of a default entvty. 5. Multple Frame Tet of Medan CFAR Algorthm The propoed Medan CFAR Algorthm ha been teted on a mult-frame baed Kmbla boat acoutc gnal whch hown n Fg. 9. The effect of Medan CFAR wndow ze on the threhold vector the mprovement of fnal detecton after mult-frame fuon have been teted and tuded n th ecton. a Kmbla boat gnal pectrum over multple frame b Kmbla boat gnal pectrum threhold mage obtaned by applyng Medan CFAR wndow ze of 3 on orgnal gnal pectrum. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 3

15 Daha Cheng c Kmbla boat gnal pectrum threhold mage obtaned by applyng a Medan CFAR wndow ze of 5 on orgnal gnal pectrum. d Kmbla boat gnal pectrum threhold mage obtaned by applyng a Medan CFAR wndow ze of 7 on orgnal gnal pectrum. FIGURE 9: Effect of Medan CFAR Wndow Sze On Threhold Sgnal. Fg. 9 a how u the Kmbla boat gnal pectrum over multple frame and Fg. 9 b c and d how u the threhold mage gnal obtaned by ung the propoed Medan CFAR algorthm wth the wndow ze of 3 5 and 7 repectvely. We can that the bgger the Medan CFAR wndow the more blurrng of the threhold mage. Eample tet reult of multple frame detecton by ung the propoed algorthm are hown n Fg. and Fg. whch nclude orgnal gnal pectrum Medan CFAR threhold mage calculated by the propoed algorthm ngle frame detecton reult mage and tme fuon reult. a Detected target frequence by ung Medan CFAR algorthm wth the wndow ze of 3 and default entvty. b Detected target frequence by ung Medan CFAR algorthm wth wndow ze of 5 and default entvty. c Detected target frequence by ung Meda CFAR algorthm wth the wndow ze of 7 and default entvty. FIGURE : Multple Frame Target Detecton Reult Fg. a b and c how u that the detecton reult of Kmbla boat acoutc gnal by ung the Medan CFAR algorthm wth wndow ze of 3 5 and 7 repectvely and wth the default entvty. We can ee that wth the ncreae of the wndow ze from 3 5 to 7 a few more frequency pece are detected wth the bgger wndow ze.e. more frequency pece detected n c than b and more frequency pece detected n b than a. Baed on the reult above we found out that a Medan CFAR wndow ze of 5 wa the bet n the three tet cae a the boat generated frequency component are correctly detected but not much noe or harmonc frequency component come n. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 33

16 Daha Cheng The multple frame fuon reult of the gnal hown n Fg. are hown n Fg.. a Integrated detected target frequency component wth Medan CFAR algorthm wndow ze of 3 and default entvty. b Integrated detected target frequency component wth Medan CFAR algorthm wndow ze of 5 and default entvty c Integrated detected target frequency component wth Medan CFAR algorthm wndow ze of 7 and default entvty. FIGURE : Multple Frame Target Frequency Detecton And Fuon Reult. Fg. a b and c how u the fuon-of-detecton reult on Kmbla boat acoutc gnal by ung the propoed Medan CFAR algorthm wth wndow ze of 3 5 and 7 repectvely and wth the default entvty. We can ee that the correct detecton rate of the man frequency component about 6 z n th tet cae are 9% / 96% / and 96% / repectvely wth Fg. a b and c. In th cae the ze of Medan CFAR wndow wll be choen baed on the ablty of retance to nterference etent gnal or noe pe on t Medan CFAR threhold calculaton. For eample the Medan CFAR Algorthm wth the wndow ze of 3 can ret one nterference etent gnal or noe pe; the Medan CFAR Algorthm wth the wndow ze of 5 can ret two nterference wherea the Medan CFAR Algorthm wth the wndow ze of 7 can ret three. Baed on the analy above we beleve that overall a Medan CFAR wndow ze of 5 the bet trade-off n all thee eperment. 5.3 Robut Tet of The ropoed Medan CFAR and Mult-Frame Fuon Algorthm The robutne of the propoed Medan CFAR and mult-frame fuon ha been etenvely teted on varou dfferent real acoutc gnal whch nclude Ferry aad aad Reef heron Reef heron and Kuala Lumpur boat gnal and Whte Gauan oe. The epermental reult hown n thee tet nclude gnal pectrum mage Medan CFAR threhold mage detected frequency component and frame tme fuon reult Ferry Boat Sgnal Multple Frame Detecton and Fuon Tet The propoed Medan CFAR and mult-frame fuon algorthm ha been teted on Ferry boat gnal and the tet reult of the Ferry tet cae wth multple frame detecton and fuon are hown n Fg.. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 3

17 Daha Cheng a Ferry boat gnal pectrum over multple frame b Ferry gnal pectrum threhold mage calculated by propoed Medan CFAR algorthm wth wndow ze of 5 c Detected target frequency component by ung the propoed Medan CFAR algorthm wth wndow ze of 5 and default entvty d Integrated detected target frequency component wth frame tme FIGURE : Multple frame frequency component detecton and fuon reult Ferry gnal by ung the propoed adaptve CFAR algorthm wth wndow ze of 5. Fg. a how u that the Ferry boat gnal ha a pretty wde frequency band whch pread between about 6 to 5 z wth the man frequency component at about z and the trength of thee frequency component are between to 5 db. Fg. b how u the Medan CFAR threhold mage of Fg. a n whch we can ee that the hgher the bacground noe the hgher the threhold and threhold mage trength value are between 5 to 5 db. Fg. c how u the detected target frequency component by ung the propoed Medan CFAR Algorthm n whch we can ee that the man frequency around z ha been uccefully detected. Some other frequency component between 6 to 5 z are alo uccefully detected. Fg. d how u the ntegrated detected target frequency component of Fg. c n whch we can ee that the detecton rate of the two bgget frequency component around and 7 z are 55% / and 3% 7/ and thee two man frequency component are fnally uccefully detected by vector dtrbuton normalzaton and fnal threholdng and ther detected frequence are 7.6 z and 39.8 z. Fg. d alo how u that there are ome frequency component between 6 and 5 z n whch ther detecton rate are relatvely lower and they dd not cro the fnal threhold after dtrbuton normalzaton. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 35

18 Daha Cheng 5.3. aad Boat Sgnal Multple Frame Detecton and Fuon Tet The propoed Medan CFAR and mult-frame fuon algorthm ha alo been teted on aad boat gnal. The tet reult of the aad tet cae wth multple frame detecton and fuon are hown n the Fg. 3. a aad gnal pectrum over multple frame b aad gnal pectrum threhold mage calculated by the propoed Medan CFAR algorthm wth wndow ze of 5. c Detected target frequency component by ung the propoed Medan CFAR algorthm wth wndow ze of 5 and default entvty. d Integrated detected target frequency component by ung the propoed Medan CFAR algorthm wth wndow ze of 5 and default entvty FIGURE 3: Multple frame target frequency detecton and fuon reult of aad by ung the propoed Medan CFAR algorthm wth wndow ze of 5. Fg. 3 a how u that the aad boat gnal ha a pretty narrow frequency band manly located around 9 z wth ome mall pece around 58 z and the trength of thee frequency component are between 3 to 7 db. Fg. 3 b how u the Medan CFAR threhold mage of Fg. 3 a n whch we can ee that the threhold mage trength value are between 5 to 5 db. Fg. 3 c how u that the detected target frequency component by ung Medan CFAR Algorthm n whch we can ee that the man frequency component around 9 z ha been uccefully detected and a few other frequency component around 58 z are alo uccefully detected. Fg. 3 d how u the ntegrated detected target frequency component of Fg. 3 c n whch we can ee that the detecton rate of the bgget frequency component around 9 z 6% / and the man frequency component fnally uccefully detected by vector dtrbuton normalzaton and fnal threholdng and t detected frequency 9.65 z. In Fg. 3 d we can alo ee that there a frequency component around 58 z Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 36

19 Daha Cheng n whch the detecton rate relatvely lower and t dd not cro the fnal threhold after dtrbuton normalzaton aad Boat Sgnal Multple Frame Detecton Tet The propoed Medan CFAR and mult-frame fuon algorthm ha been teted on aad boat gnal and the tet reult of the aad tet cae wth multple frame detecton and fuon are hown n Fg.. a aad boat gnal pectrum over multple frame b aad gnal pectrum threhold mage calculated by ung the propoed Medan CFAR algorthm wth wndow ze of 5 c Detected target frequency component by ung the propoed Medan CFAR algorthm wth wndow ze of 5 and default entvty d Integrated detected target frequency component by ung the propoed Medan CFAR algorthm wth wndow ze of 5 and default entvty FIGURE : Multple frame target frequency detecton and fuon reult of aad by ung the propoed Medan CFAR Algorthm wth wndow ze of 5. Fg. a how u that the aad boat gnal ha a dvere frequency dtrbuton and the man boat generated frequency component are around 7 z wth ome frequency ncreang and decreang probably due to the acceleratng or lowng down of the boat and the trength of thee frequency component are between 3 to 7 db. There alo ome clutter noe pread between 5 to z whch are defntely not boat-generated frequency component. Fg. b how u the threhold mage of Fg. a that calculated by the propoed adaptve Medan CFAR algorthm n whch we can ee that the threhold mage trength value are between 5 to 5 db whch are much maller than the mamum value of gnal component of 8 db. We can alo ee that the threhold around the unnown clutter noe area between Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 37

20 Daha Cheng 5 to z are very trong about 5 db whch are very helpful at removal of poble fale detecton. Fg. c how u the detected target frequency component by ung Medan CFAR Algorthm n whch we can ee that the man frequency around 7 z ha been uccefully detected and the fale detecton pobly caued by ome other unnown clutter noe frequency component between 5 to z are uccefully avoded The clutter wll probably caue fale detecton f we ue contant threhold that normally ued n acoutc gnal proceng and detecton.. Fg. d how u the ntegrated detected target frequency component of Fg. c n whch we can ee that the detecton rate of the three bgget frequency component around 7 z are 68% about 65 z 5% around z and 3% around 3 z and the bgget man frequency component wa fnally uccefully detected by vector dtrbuton normalzaton and fnal threholdng and t detected frequency 65.8 z. In Fg. d we can alo ee that the econd and thrd bgget frequency component dd not cro the fnal threhold under the 5% fnal detecton threhold after dtrbuton normalzaton Reef eron Boat Sgnal Multple Frame Detecton and Fuon Tet The propoed Medan CFAR and mult-frame fuon algorthm ha been teted on Reef eron boat gnal and the tet reult of the Reef eron tet cae wth multple frame detecton and fuon are hown n Fg. 5. a Reef eron boat gnal pectrum over multple frame b Reef eron boat gnal pectrum threhold mage calculated by the propoed Medan CFAR algorthm wth wndow ze of 5 c Detected target frequency component by ung the propoed Medan CFAR algorthm wth the wndow ze of 5 and default entvty d Integrated detected target frequency component by ung the propoed Medan CFAR algorthm wth the wndow ze of 5 and default entvty FIGURE 5: Multple frame target frequency detecton and fuon reult of Reef heron by ung the propoed Medan CFAR algorthm wth wndow ze of 5 Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 38

21 Daha Cheng Fg. 5 a how u that the Reef eron boat gnal ha pretty looely dtrbuted frequency component n a very broad band range n term of our obervaton range whch pread from about to z wth the tronget frequency component are around 68 and 5 z and the trength of thee frequency component are between 3 to 5 db. Fg. 5 b how u the Medan CFAR threhold mage of Fg. 5 a n whch we can ee that the threhold mage trength value are between to db. Fg. 5 c how u the detected target frequency component by ung Medan CFAR Algorthm n whch we can ee that the two man frequency component at around 68 and 5 z have been uccefully detected and ome other frequency component between to 5 z are alo croed the Medan CFAR threhold. Fg. 5 d how u the ntegrated detected target frequency component of Fg. 5 c n whch we can ee that the detecton rate of the bgget frequency component around 68 z 58% and th man frequency component wa fnally uccefully detected by vector dtrbuton normalzaton and fnal threholdng and t detected frequency 68.6 z. In Fg. 5 d we can alo ee that there are ome frequency component between and 5 z n whch the detecton rate are relatvely lower and that dd not cro the fnal threhold after dtrbuton normalzaton Reef eron boat gnal multple frame detecton and fuon tet The propoed Medan CFAR and mult-frame fuon algorthm ha been teted on Reef eron boat gnal and the tet reult the Reef eron tet cae wth multple frame detecton and fuon are hown n Fg. 6. a Reef eron boat gnal pectrum over multple frame b Reef eron boat gnal pectrum threhold mage calculated by the propoed Medan CFAR algorthm wth the wndow ze of 5 Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 39

22 Daha Cheng c Detected target frequency component by ung the propoed Medan CFAR algorthm wth wndow ze of 5 and a default entvty d Integrated detected target frequency component by ung the propoed Medan CFAR algorthm wth wndow ze of 5 and a default entvty. FIGURE 6: Multple frame target frequency component detecton and fuon reult Reef eron by ung the propoed Medan CFAR algorthm wth wndow ze of 5. Fg. 6 a how u that there are two man frequency component around 8 and 7 z n the Reef eron boat gnal and there are ome frequency hft around 8 z probably becaue of the change of the peed of boat engne. And there are ome unnown clutter frequency component that are around 8 z wth the trength between 3 to 5 db. Fg. 6 b how u that Medan CFAR threhold mage of Fg. 6 a n whch we can ee that the threhold mage trength value are between to 5 db. Fg. 6 c how u that the detected target frequency component by ung Medan CFAR Algorthm n whch we can ee that the two man frequency component at around 8 and 7 z have been uccefully detected but ome other ea clutter frequency component are too low to cro the Medan CFAR threhold n whch ome fale detecton are avoded. Fg. 6 d how u the ntegrated detected target frequency component of Fg. 6 c whch how u that there are everal frequency component around 7 z and the detecton rate of the bgget one around 68 z above 65%. And the man frequency component that were uccefully detected fnally by vector dtrbuton normalzaton and fnal threholdng are 78z and 8z. In Fg. 6 d we can alo ee that the econd bgget frequency component around 7 z for whch t the detecton rate relatvely lower dd not cro the fnal threhold after dtrbuton normalzaton under the 5% fnal detecton threhold Kuala Lumpur Boat Sgnal Multple Frame Tet The propoed Medan CFAR and Mult-Frame Fuon Algorthm ha been teted on Kuala Lumpur boat gnal and the tet reult of the Kuala Lumpur tet cae wth multple frame detecton and fuon are hown n Fg. 7. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8

23 Daha Cheng a Kuala Lumpur boat gnal pectrum over multple frame b Kuala Lumpur boat gnal pectrum threhold mage calculated by the propoed Medan CFAR algorthm wth the wndow Sze of 5 c Detected target frequency component ung the propoed Medan CFAR algorthm wth the wndow ze of 5 and a default entvty d Integrated detected target frequency component by ung the propoed Medan CFAR algorthm wth the wndow Sze of 5 and a default entvty FIGURE 7: Multple frame target frequency detecton fuon reult of Kuala Lumpur by ung the propoed Medan CFAR algorthm wth the wndow ze of 5 Fg. 7 a how u that the Kuala Lumpur boat gnal ha one clear man frequency trp component whch are located around 3 around 3 z there ome frequency quc ncreae n a very hort tme probably becaue the peed of boat engne wa ncreang and the trength of thee frequency component are between 3 to 5 db. Fg. 7 b how u the Medan CFAR threhold mage of Fg. 6 a n whch we can ee that the threhold mage trength value are between 5 to 5 db. Fg. 7 c how u the detected target frequency component by ung Medan CFAR Algorthm n whch we can ee that the man frequency component at around 8z have been uccefully detected and ome other frequency component a lttle below 8 z are alo uccefully detected. Fg. 7 d how u the ntegrated detected target frequency component of Fg. 7 c n whch we can ee the detecton rate of the bgget frequency component around 68 z 65% and th man frequency component wa fnally uccefully detected by vector dtrbuton normalzaton and fnal threholdng and t detected frequency 37.93z. In Fg. 7 d we can alo ee ome other frequency component ut below z n whch the detecton rate are relatvely lower and dd not cro the fnal threhold after dtrbuton normalzaton under the 5% fnal detecton threhold. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8

24 Daha Cheng o gnal wth only whte Gauan noe tet - multple frame tet reult The propoed Medan CFAR and mult-frame fuon algorthm ha been teted wth o Sgnal but only Whte Gauan oe tuaton and the tet reult of the Whte Gauan oe tet cae wth multple frame detecton and fuon are hown n Fg. 8. a Whte Gauan oe gnal pectrum over multple frame b Whte Gauan oe gnal pectrum threhold Image calculated by the propoed Medan CFAR algorthm wth the wndow ze of 5 c Detected target frequence ung the propoed Medan CFAR algorthm wth the wndow ze of 5 and a default entvty d Integrated detected target frequence ung the propoed Medan CFAR algorthm wth the wndow ze of 5 and a default entvty FIGURE 8: Multple frame target detecton fuon reult of no gnal but only gauan noe Fg. 8 how u that no target detected and proved that the propoed Medan CFAR and Mult-Frame Fuon Algorthm can deal wth the o Sgnal cae very well whch often the cae n a very quet ocean area wth no boat traffc. Th due to the fact that the CFAR algorthm baed on the dea of comparon of each frequency bn pel wth t neghborhood bacground noe. In th tet cae the dfference between the value of every frequency bn pel bn and ther threhold too mall to cro the detecton threhold. 6. RELATED WORKS AD DISCUSSIO In th paper a novel Adaptve Contant Fale Alarm Rate ACFAR and ot Detecton Fuon algorthm have been propoed for an effectve automatc detecton of marne vehcle generated acoutc gnal pectrum gnature. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8

25 Daha Cheng. Compared wth the tradtonal average CFAR algorthm CA CFAR and CAGO CFAR[3 the propoed Medan CFAR algorthm ha the ablty to remove the effect of gnal component whle etmatng the bacground noe o the etmated noe level much more accurate epecally when there gnal component n certan frequency bn.. Compared wth ome other hp gnature meaurement algorthm uch a Kl Woo Chung etc. DEMO Acoutc Shp Sgnature Meaurement [3 the propoed detecton algorthm ha etremely low fale alarm almot never ha any fale alarm becaue of the accurate etmate the bacground noe. 3. Compared wth amed Komar Alae and aan Far tattcal algorthm [35 the propoed algorthm much eaer for future engneerng applcaton. 7. COCLUSIOS AD FUTURE WORK In th paper an Adaptve Contant Fale Alarm Rate ACFAR and pot detecton fuon algorthm have been propoed baed on the eyman-earon crteron for an effectve automatc detecton of marne vehcle generated acoutc gnal pectrum gnature n whch a low contant fale alarm rate ept wth etremely hgh detecton rate. The propoed algorthm have been teted on real acoutc gnal recorded from hydrophone called Kmbla Ferry aad aad Reef heron Reef heron and Kuala Lumpur marne vehcle gnal and alo on a pattern of whte noe. The tattcal analy and epermental reult howed that the propoed algorthm ha ept a very low fale alarm rate and etremely hgh detecton rate. The followng concluon can alo be drawn: The propoed adaptve CFAR algorthm ued to detect gnal pectrum gnature n ngle frame whch wll eep our automatc target detecton ytem at lower and contant fale alarm rate. Th algorthm epecally good for detectng LOFAR target frequency component. The bgger the Medan CFAR wndow the lower frequency component n the threhold gnal mage. In our eperment the Medan CFAR wndow ze of 5 approprate for mot cae. 3 A magntude n the frequency doman normalzaton and db amplfcaton are ued to eep our automatc detector more robut. Wth the default entvty value mot marne vehcle generated gnal frequency component are correctly detected. Decreang entvty value mae the fale detecton rate alarm rate lower and le frequency component wll be detected at the ame tme. 5 The fuon of ngle frame detected frequency component wll mae the detecton much more robut. For eample wth the fuon of frame the poblty of correct target detecton ncreae dramatcally. 6 In order to deal wth varou nd of detected target tuaton and ncreae the probablty of p target detecton Integrated target vector normalzaton and db amplfcaton are ued to eep our fnal detecton more robut and relable ncreae probablty of correct detecton.. 7 In the eperment the detected boat generated frequence of Kmbla Ferry aad aad Reef heron Reef heron and Kuala Lumpur are z 7.6 z and 39.8 z 9.65 z 65.8 z z 78.37z and 8.9 z and z repectvely whch correpond very cloely to the ground truth. 8 In the o Sgnal wth only Whte Gauan oe tet cae no target frequency component detected. That proved that the propoed Medan CFAR and Mult-Frame Fuon Algorthm can deal wth o Sgnal cae very well. That becaue of the CFAR algorthm baed on the dea of comparon of each frequency bn pel wth t neghborhood bacground noe. In th tet cae the dfference between the value of every frequency bn pel bn and ther threhold too mall to cro the detecton threhold. Future wor: Recognton - The detected pectrum gnature can be ued for hp recognton and tracng n the future n whch the tudy of mlarty meaure between hp pectrum p p Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 3

26 Daha Cheng gnature and the neural networ can alo be pobly appled for the recognton of detected hp baed on a databae of collected pectrum gnature. Tracng-The propoed real tme proceng and detectng baed onar can be connected nto a worldwde underea networ n whch the hp around each onar can be detected traced and dplayed n a control center. 3 Array proceng - Sonar array proceng baed on the propoed algorthm a a buldng bloc can alo be ued to ncreae the SR of nput gnal or detect the drecton of ncomng hp 8. ACKOWLEDGMET The reearch upported by 7 Changhu Scentfc and Technology Development lan roect CQ7 and the tet data wa provded by Sonarcom TY LTD n Autrala. 9. REFERECES [ S. Lawrence Marple Jr. "Dgtal Spectral Analy wth Applcaton". rentce all Inc [ Chan Y. T. "Underwater Acoutc Data roceng" ATO ASI Sere Kluwer Academc ublher. [3 A. D. Wate "Sonar for ractng Engneer" John Wlley & Son LTD. [ Urc R. J rncple of Underwater Sound. ew Yor McGraw-ll Boo Company. [5 Lurton X.. An Introducton to Underwater Acoutc: rncple and Applcaton. Chcheter UK Sprnger/ra. [6 Etter. C. 99. Underwater Acoutc Modelng: rncple Technque and Applcaton. ew Yor Elever. [7 Burdc W. S. 98 "Underwater Acoutc Sytem Analy" rentce-all Englewood Clf J. [8 J. X. Qu L. Zheng Y. C. Wang "Reearch on hp-radated noe beat tune" Techncal Acoutc vol. 33 no. pp [9 F. S. Zhang D. Feng "Fuon and etracton of modulaton feature from hp radated-noe baed on wavelet pacet and ZFFT" Electronc World vol. no. pp [ X. W. Luo S. L. Fang "Feature etracton from non-tatonary ampltude modulated broadband gnal ung the lbert-uang tranform" Sgnal roceng vol. 7 no. 6 pp [ Xueyao L; Fupng Zhu; arbn Eng. and arbn Unverty Applcaton of the zero-crong rate LOFAR pectrum and wavelet to the feature etracton of pave onar gnal roceedng of the 3rd World Congre on Intellgent Control and Automaton. vol. pp [ G. Q. Wu "Shp radated-noe recognton I the overall framewor analy and etracton of lne-pectrum" Acta Acoutca vol. 3 no. 5 pp [3 Y. S. Cheng X. Gao. Lu "A method for hp propeller blade-number recognton baed on template matchng" TechncaI Acoutc vol. 9 no. pp Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8

27 Daha Cheng [ eng.c. Long F. and Dng C. Feature electon baed on mutual nformaton: crtera of ma-dependency ma-relevance and mn-redundancy IEEE Tranacton on attern Analy and Machne Intellgence Vol. 7 o. 8 pp [5 Roholng. "Radar CFAR Threholdng n Clutter and Multple Target Stuaton" IEEE Tranacton on Aeropace and Electronc Sytem Vol. AES-9 o. July 983 pp [6 Merrll I Soln "Introducton to Radar Sytem". McGraw-ll Boo Company 98. [7 S. Wang J. X. Qu S. J. Wang "Enhancement of hp radated noe DEMO pectrum SR baed on correlaton properte theory of prncple of ytem_dynamc" Shp Scence and Technology vol. 35 no. 8 pp [8 Y. S. Cheng Y. C. Wang "DEMO analy of underwater target radaton noe baed on modern gnal proceng" Techncal Acoutc vol. 5 no. pp [9 Erc Daha Cheng Subhah Challa Xuanchen Tang and Xaohu Lu "on-cooperatve Obect Detecton n Sea Ung Acoutc Senor" accepted by the Dgtal Image Computng: Technque and Applcaton -3 December Sydney Autrala. DICTA pp9-3. [ Erc Daha Cheng Mamo ccard and Tony Jan "Boat-Generated Acoutc Target Sgnal Detecton by Ue Of An Adaptve Medan CFAR and Mult-Frame Integraton Algorthm" The 5 European Sgnal roceng Conference EUSICO-5 September -8 Antalya Turey. [ Erc D. Cheng Mamo ccard and Tony Jan "Stochatc Boat-Generated Acoutc Target Sgnal Detecton n Tme-Frequency Doman" IEEE Internatonal Sympoum on Sgnal roceng and Informaton Technology ISSIT Rome Italy December. [ Vera. Behar "Adaptve CFAR I roceor for Radar Target Detecton n ule Jammng" Journal of VLSI Sgnal roceng Vol. 6 pp [3 Levanon. Shor M. "Order Stattc CFAR for Webull Bacground" IEE roceedng Vol. 37 o. 3 June 99 pp [ Roholng. "Radar CFAR Threholdng n Clutter and Multple Target Stuaton" IEEE Tranacton on Aeropace and Electronc Sytem Vol. AES-9 o. July 983 pp [5 I.G. roopeno F.J. Yanovy L.. Lgthart "Adaptve Algorthm for Weather Radar" roceedng of the European Radar Conference EuRAD pp [6 A. D. Whalen Detecton of Sgnal n oe. ew Yor Academc 97 pp [7. L.Van Tree "Detecton Etmaton and Modulaton Theory". art I. ew Yor Wly 968 pp [8 enry Star John W. Wood "robablty and random proce wth applcaton to gnal proceng" rentce all 3rd edton. [9 M. D. Srnach. K. Raaearan and R. Vwanathan "Introducton to tattcal gnal proceng wth applcaton" rentce all Englewood Clff ew Jerey. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 5

28 Daha Cheng [3 R. Cucchara C. Grana M. ccard and A. rat "Stattc and Knowledge-baeetcd Movng Obect Detecton n Traffc Scene" n roc. of ITSC- - The 3rd Annual IEEE Conference on Intellgent Tranportaton Sytem Oct. -5 Dearborn MI USA pp [3 Charle W. Therren "Dcrete Random Sgnal and Stattcal Sgnal roceng" rentce all Englewood Clff J 763. [3. M. Fnn and R. S. Johnon "Adaptve Detecton Mode wth Threhold Control a a Functon of Spatally Sampled Clutter Level Etmate" RCA Revew Vol. 9 o. 3 pp. September 968. [33 Rtcey J. A. "erformance Analy of the Cenored Mean-Level Detector" IEEE Tranacton on Aeropace and Electronc Sytem Vol. AES- o. 6 July 986 pp [3 Advance n Acoutc and Vbraton Volume Artcle ID page [35 amed Komar Alae and aan Far "ave Sonar Target Detecton Ung Stattcal Clafer and Adaptve Threhold" Appl. Sc ; do:.339/app86. [36 Davd C. Swanon "Sgnal roceng for Intellgent Senor Sytem" Marcel Deer. Inc. [37 Rchard O. elen "Sonar Sgnal roceng" Artech oue. [38 elon R. O. 99. Sonar Sgnal roceng. orwood MA Artech oue. [39 Robnon A. R. and D. Lee Ed. 99. Oceanography and Acoutc redcton and ropagaton Model. Modern Acoutc and Sgnal roceng. Woodbury Y AI re. [ R. O. elen "Sonar Sgnal Analy". Boton MA Artech oue 99 pp [ Stergo Stergopoulo "Advanced Sgnal roceng andboo" CRC re. [ Todd K. Moon and Wynn C. Strlng "Mathematcal Method and Algorthm for Sgnal roceng" rentce-allupper Saddle Rver J 758. Sgnal roceng: An Internatonal Journal SIJ Volume : Iue : 8 6

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo. ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract

More information

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features On-Lne Fault Detecton n Wnd Turbne Transmsson System usng Adaptve Flter and Robust Statstcal Features Ruoyu L Remote Dagnostcs Center SKF USA Inc. 3443 N. Sam Houston Pkwy., Houston TX 77086 Emal: ruoyu.l@skf.com

More information

PERFORMANCE ANALYSIS OF PARALLEL ALGORITHMS

PERFORMANCE ANALYSIS OF PARALLEL ALGORITHMS Software Analye PERFORMANCE ANALYSIS OF PARALLEL ALGORIHMS Felcan ALECU PhD, Unverty Lecturer, Economc Informatc Deartment, Academy of Economc Stude, Bucharet, Romana E-mal: alecu.felcan@e.ae.ro Abtract:

More information

ARTICLE IN PRESS. JID:COMAID AID:1153 /FLA [m3g; v 1.79; Prn:21/02/2009; 14:10] P.1 (1-13) Computer Aided Geometric Design ( )

ARTICLE IN PRESS. JID:COMAID AID:1153 /FLA [m3g; v 1.79; Prn:21/02/2009; 14:10] P.1 (1-13) Computer Aided Geometric Design ( ) COMAID:5 JID:COMAID AID:5 /FLA [mg; v 79; Prn:/0/009; 4:0] P -) Computer Aded Geometrc Degn ) Content lt avalable at ScenceDrect Computer Aded Geometrc Degn wwwelevercom/locate/cagd Fat approach for computng

More information

Multifunction Phased Array Radar Resource Management: Real-Time Scheduling Algorithm

Multifunction Phased Array Radar Resource Management: Real-Time Scheduling Algorithm Journal of Computatonal Informaton Sytem 7:2 (211) 385-393 Avalable at http://www.jofc.com Multfuncton Phaed Array Radar Reource Management: Real-me Schedulng Algorm Janbn LU 1,, Hu XIAO 2, Zemn XI 1,

More information

An Alternative Way to Measure Private Equity Performance

An Alternative Way to Measure Private Equity Performance An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

More information

A Novel Architecture Design of Large-Scale Distributed Object Storage System

A Novel Architecture Design of Large-Scale Distributed Object Storage System Internatonal Journal of Grd Dtrbuton Computng Vol.8, No.1 (2015), pp.25-32 http://dx.do.org/10.14257/gdc.2015.8.1.03 A Novel Archtecture Degn of Large-Scale Dtrbuted Obect Storage Sytem Shan Yng 1 and

More information

Development and use of prediction models in Building Acoustics as in EN 12354. 1 Introduction. 2 EN 12354, part 1 & 2. 2.2 Lightweight single elements

Development and use of prediction models in Building Acoustics as in EN 12354. 1 Introduction. 2 EN 12354, part 1 & 2. 2.2 Lightweight single elements evelopment and ue of predcton model n Buldng Acoutc a n EN 1354 Eddy TNO Scence and Indutry, P.O. Box 155, N-600 A elft, The Netherland, eddy.gerreten@tno.nl Improvng the acoutc clmate n buldng an mportant

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

New method for grain size characterization of a multi-crystalline silicon ingot

New method for grain size characterization of a multi-crystalline silicon ingot New method for gran ze characterzaton of a mult-crytallne lcon ngot Maxme Forter, Erwann Fourmond, Jean-Mare Lebrun, Roland Enhau, Jed Kraem, Mutapha Lemt To cte th veron: Maxme Forter, Erwann Fourmond,

More information

Calculation of Sampling Weights

Calculation of Sampling Weights Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample

More information

THE ANALYSIS AND OPTIMIZATION OF SURVIVABILITY OF MPLS NETWORKS. Mohammadreza Mossavari, Yurii Zaychenko

THE ANALYSIS AND OPTIMIZATION OF SURVIVABILITY OF MPLS NETWORKS. Mohammadreza Mossavari, Yurii Zaychenko Internatonal Journal "Informaton Theore & Applcaton" Vol5 / 28 253 TE ANALYSIS AND OTIMIATION OF SURVIVABILITY OF MLS NETWORS Mohammadreza Moavar, Yur aychenko Abtract: The problem of MLS network urvvablty

More information

T1 Estimates SAT - 2006

T1 Estimates SAT - 2006 T1 Etmate SAT - 006 Tax and Lmoune Servce (TL) NAICS : 4853** by Javer Oyarzun BSMD Stattc Canada 007-1-1 1. Introducton 1.1 Ue of admntratve data Over the lat few year, Stattc Canada (STC) ha been accentuatng

More information

Abstract. 2.2. Adjusted PPM.

Abstract. 2.2. Adjusted PPM. Effectvene of Avance an Authentcate Packet Markng Scheme for Traceback of Denal of Servce Attack Blal Rzv an Emmanuel Fernánez-Gaucheran Department of Electrcal & Computer Engneerng &Computer Scence Unverty

More information

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure

More information

An Enhanced Super-Resolution System with Improved Image Registration, Automatic Image Selection, and Image Enhancement

An Enhanced Super-Resolution System with Improved Image Registration, Automatic Image Selection, and Image Enhancement An Enhanced Super-Resoluton System wth Improved Image Regstraton, Automatc Image Selecton, and Image Enhancement Yu-Chuan Kuo ( ), Chen-Yu Chen ( ), and Chou-Shann Fuh ( ) Department of Computer Scence

More information

Damage detection in composite laminates using coin-tap method

Damage detection in composite laminates using coin-tap method Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The con-tap test has the

More information

Frequency Selective IQ Phase and IQ Amplitude Imbalance Adjustments for OFDM Direct Conversion Transmitters

Frequency Selective IQ Phase and IQ Amplitude Imbalance Adjustments for OFDM Direct Conversion Transmitters Frequency Selectve IQ Phase and IQ Ampltude Imbalance Adjustments for OFDM Drect Converson ransmtters Edmund Coersmeer, Ernst Zelnsk Noka, Meesmannstrasse 103, 44807 Bochum, Germany edmund.coersmeer@noka.com,

More information

ITS-90 FORMULATIONS FOR VAPOR PRESSURE, FROSTPOINT TEMPERATURE, DEWPOINT TEMPERATURE, AND ENHANCEMENT FACTORS IN THE RANGE 100 TO +100 C.

ITS-90 FORMULATIONS FOR VAPOR PRESSURE, FROSTPOINT TEMPERATURE, DEWPOINT TEMPERATURE, AND ENHANCEMENT FACTORS IN THE RANGE 100 TO +100 C. ITS-90 FORMULATIONS FOR VAPOR PRESSURE, FROSTPOINT TEMPERATURE, DEWPOINT TEMPERATURE, AND ENHANCEMENT FACTORS IN THE RANGE 100 TO +100 C Bob Hardy Thunder Scentfc Corporaton, Albuquerque, NM, USA Abtract:

More information

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedo-cho

More information

Vision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION

Vision Mouse. Saurabh Sarkar a* University of Cincinnati, Cincinnati, USA ABSTRACT 1. INTRODUCTION Vson Mouse Saurabh Sarkar a* a Unversty of Cncnnat, Cncnnat, USA ABSTRACT The report dscusses a vson based approach towards trackng of eyes and fngers. The report descrbes the process of locatng the possble

More information

Basic Principle of Buck-Boost

Basic Principle of Buck-Boost Bac Prncple of Buck-Boot he buck-boot a popular non-olated nvertng power tage topology, ometme called a tep-up/down power tage. Power upply degner chooe the buck-boot power tage becaue the requred output

More information

Pass by Reference vs. Pass by Value

Pass by Reference vs. Pass by Value Pa by Reference v. Pa by Value Mot method are paed argument when they are called. An argument may be a contant or a varable. For example, n the expreon Math.qrt(33) the contant 33 paed to the qrt() method

More information

An Integrated Resource Management and Scheduling System for Grid Data Streaming Applications

An Integrated Resource Management and Scheduling System for Grid Data Streaming Applications An Integrated eource Management and Schedulng Sytem for Grd Data Streamng Applcaton Wen Zhang, Junwe Cao 2,3*, Yheng Zhong,3, Lanchen Lu,3, and Cheng Wu,3 Department of Automaton, Tnghua Unverty, Bejng

More information

Forecasting the Direction and Strength of Stock Market Movement

Forecasting the Direction and Strength of Stock Market Movement Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems

More information

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel

More information

Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008

Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008 Rsk-based Fatgue Estmate of Deep Water Rsers -- Course Project for EM388F: Fracture Mechancs, Sprng 2008 Chen Sh Department of Cvl, Archtectural, and Envronmental Engneerng The Unversty of Texas at Austn

More information

A Multi-mode Image Tracking System Based on Distributed Fusion

A Multi-mode Image Tracking System Based on Distributed Fusion A Mult-mode Image Tracng System Based on Dstrbuted Fuson Ln zheng Chongzhao Han Dongguang Zuo Hongsen Yan School of Electroncs & nformaton engneerng, X an Jaotong Unversty X an, Shaanx, Chna Lnzheng@malst.xjtu.edu.cn

More information

An Efficient Recovery Algorithm for Coverage Hole in WSNs

An Efficient Recovery Algorithm for Coverage Hole in WSNs An Effcent Recover Algorthm for Coverage Hole n WSNs Song Ja 1,*, Wang Balng 1, Peng Xuan 1 School of Informaton an Electrcal Engneerng Harbn Insttute of Technolog at Weha, Shanong, Chna Automatc Test

More information

A Survey of Automatic Modulation Classification Techniques: Classical Approaches and New Trends

A Survey of Automatic Modulation Classification Techniques: Classical Approaches and New Trends Survey of utomatc Modulaton Clafcaton Technque: Clacal pproache and New Trend Octava. Dobre, l bd, Yeheel Bar-Ne and We Su 3 Faculty of Engneerng and ppled Scence, Memoral Unverty of Newfoundland St. John,

More information

Dynamic Control of Data Streaming and Processing in a Virtualized Environment

Dynamic Control of Data Streaming and Processing in a Virtualized Environment > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 1 Dynamc Control of Data Streamng and Proceng n a Vrtualzed Envronment Junwe Cao, Senor Member, IEEE, Wen Zhang,

More information

Time Delayed Independent Component Analysis for Data Quality Monitoring

Time Delayed Independent Component Analysis for Data Quality Monitoring IWSSIP 1-17th Internatonal Conference on Systems, Sgnals and Image Processng Tme Delayed Independent Component Analyss for Data Qualty Montorng José Márco Faer Sgnal Processng Laboratory, COE/Pol Federal

More information

Luby s Alg. for Maximal Independent Sets using Pairwise Independence

Luby s Alg. for Maximal Independent Sets using Pairwise Independence Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent

More information

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by 6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng

More information

IMPACT ANALYSIS OF A CELLULAR PHONE

IMPACT ANALYSIS OF A CELLULAR PHONE 4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng

More information

Implementation of Deutsch's Algorithm Using Mathcad

Implementation of Deutsch's Algorithm Using Mathcad Implementaton of Deutsch's Algorthm Usng Mathcad Frank Roux The followng s a Mathcad mplementaton of Davd Deutsch's quantum computer prototype as presented on pages - n "Machnes, Logc and Quantum Physcs"

More information

The OC Curve of Attribute Acceptance Plans

The OC Curve of Attribute Acceptance Plans The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4

More information

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

Research Note APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES * Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC

More information

Applied Research Laboratory. Decision Theory and Receiver Design

Applied Research Laboratory. Decision Theory and Receiver Design Decson Theor and Recever Desgn Sgnal Detecton and Performance Estmaton Sgnal Processor Decde Sgnal s resent or Sgnal s not resent Nose Nose Sgnal? Problem: How should receved sgnals be rocessed n order

More information

What is Candidate Sampling

What is Candidate Sampling What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

More information

Quantitative Evaluation of Porosity in Aluminum Die Castings by Fractal Analysis of Perimeter

Quantitative Evaluation of Porosity in Aluminum Die Castings by Fractal Analysis of Perimeter Materal Tranacton, Vol. 49, No. 4 (28) pp. 782 to 786 #28 The Japan Inttute of Metal Quanttatve Evaluaton of Poroty n Alumnum De Catng by Fractal Analy of Permeter Yohhko Hanga 1 and Sochro Ktahara 2 1

More information

A Secure Password-Authenticated Key Agreement Using Smart Cards

A Secure Password-Authenticated Key Agreement Using Smart Cards A Secure Password-Authentcated Key Agreement Usng Smart Cards Ka Chan 1, Wen-Chung Kuo 2 and Jn-Chou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,

More information

An Analysis of Central Processor Scheduling in Multiprogrammed Computer Systems

An Analysis of Central Processor Scheduling in Multiprogrammed Computer Systems STAN-CS-73-355 I SU-SE-73-013 An Analyss of Central Processor Schedulng n Multprogrammed Computer Systems (Dgest Edton) by Thomas G. Prce October 1972 Techncal Report No. 57 Reproducton n whole or n part

More information

To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.

To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently. Corporate Polces & Procedures Human Resources - Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:

More information

How To Understand Propect Theory And Mean Variance Analysis

How To Understand Propect Theory And Mean Variance Analysis Invetment Management and Fnancal Innovaton, Volume 6, Iue 1, 2009 Enrco De Gorg (Swtzerland ), Thorten Hen (Swtzerland) Propect theory and mean-varance analy: doe t make a dfference n wealth management?

More information

Lecture #21. MOS Capacitor Structure

Lecture #21. MOS Capacitor Structure Lecture #21 OUTLINE The MOS apactor Electrotatc Readng: oure Reader EE130 Lecture 21, Slde 1 MOS apactor Structure MOS capactor (croectonal vew _ TE x EE130 Lecture 21, Slde 2 Typcal MOS capactor and trantor

More information

Calculating the high frequency transmission line parameters of power cables

Calculating the high frequency transmission line parameters of power cables < ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,

More information

Face Verification Problem. Face Recognition Problem. Application: Access Control. Biometric Authentication. Face Verification (1:1 matching)

Face Verification Problem. Face Recognition Problem. Application: Access Control. Biometric Authentication. Face Verification (1:1 matching) Face Recognton Problem Face Verfcaton Problem Face Verfcaton (1:1 matchng) Querymage face query Face Recognton (1:N matchng) database Applcaton: Access Control www.vsage.com www.vsoncs.com Bometrc Authentcaton

More information

Study on Model of Risks Assessment of Standard Operation in Rural Power Network

Study on Model of Risks Assessment of Standard Operation in Rural Power Network Study on Model of Rsks Assessment of Standard Operaton n Rural Power Network Qngj L 1, Tao Yang 2 1 Qngj L, College of Informaton and Electrcal Engneerng, Shenyang Agrculture Unversty, Shenyang 110866,

More information

An interactive system for structure-based ASCII art creation

An interactive system for structure-based ASCII art creation An nteractve system for structure-based ASCII art creaton Katsunor Myake Henry Johan Tomoyuk Nshta The Unversty of Tokyo Nanyang Technologcal Unversty Abstract Non-Photorealstc Renderng (NPR), whose am

More information

BERNSTEIN POLYNOMIALS

BERNSTEIN POLYNOMIALS On-Lne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful

More information

Realistic Image Synthesis

Realistic Image Synthesis Realstc Image Synthess - Combned Samplng and Path Tracng - Phlpp Slusallek Karol Myszkowsk Vncent Pegoraro Overvew: Today Combned Samplng (Multple Importance Samplng) Renderng and Measurng Equaton Random

More information

A Falling Detection System with wireless sensor for the Elderly People Based on Ergnomics

A Falling Detection System with wireless sensor for the Elderly People Based on Ergnomics Vol.8, o.1 (14), pp.187-196 http://dx.do.org/1.1457/sh.14.8.1. A Fallng Detecton System wth wreless sensor for the Elderly People Based on Ergnomcs Zhenhe e 1, ng L, Qaoxang Zhao and Xue Lu 3 1 College

More information

Optimum Design of Magnetic Inductive Energy Harvester and its AC-DC Converter

Optimum Design of Magnetic Inductive Energy Harvester and its AC-DC Converter Otmum Degn of Magnetc nductve Energy Harveter and t AC-DC Converter Qan Sun, Sumeet Patl, Stehen Stoute, Nan-Xang Sun, Brad Lehman Deartment of Electrcal and Comuter Engneerng Northeatern Unverty Boton,

More information

Recurrence. 1 Definitions and main statements

Recurrence. 1 Definitions and main statements Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

More information

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS 21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech-2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS

More information

Vehicle Detection and Tracking in Video from Moving Airborne Platform

Vehicle Detection and Tracking in Video from Moving Airborne Platform Journal of Computatonal Informaton Systems 10: 12 (2014) 4965 4972 Avalable at http://www.jofcs.com Vehcle Detecton and Trackng n Vdeo from Movng Arborne Platform Lye ZHANG 1,2,, Hua WANG 3, L LI 2 1 School

More information

Proactive Secret Sharing Or: How to Cope With Perpetual Leakage

Proactive Secret Sharing Or: How to Cope With Perpetual Leakage Proactve Secret Sharng Or: How to Cope Wth Perpetual Leakage Paper by Amr Herzberg Stanslaw Jareck Hugo Krawczyk Mot Yung Presentaton by Davd Zage What s Secret Sharng Basc Idea ((2, 2)-threshold scheme):

More information

The Design of Reliable Trust Management Systems for Electronic Trading Communities

The Design of Reliable Trust Management Systems for Electronic Trading Communities The Degn of Relale Trut Management Sytem for Electronc Tradng Communte Chryantho Dellaroca Sloan School of Management Maachuett Inttute of Technology Room E53-315 Camrdge, MA 02139 dell@mt.edu Atract:

More information

On the Optimal Control of a Cascade of Hydro-Electric Power Stations

On the Optimal Control of a Cascade of Hydro-Electric Power Stations On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;

More information

REVISTA INVESTIGACIÓN OPERACIONAL VOL., 33, NO. 3, 233-244, 2012.

REVISTA INVESTIGACIÓN OPERACIONAL VOL., 33, NO. 3, 233-244, 2012. REVISA INVESIGACIÓN OPERACIONAL VOL., 33, NO. 3, 33-44,. ORDERING POLICY FOR INVENORY MANAGEMEN WHEN DEMAND IS SOCK- DEPENDEN AND A EMPORARY PRICE DISCOUN IS LINKED O ORDER UANIY Nta H. Shah Department

More information

The Application of Fractional Brownian Motion in Option Pricing

The Application of Fractional Brownian Motion in Option Pricing Vol. 0, No. (05), pp. 73-8 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qng-xn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com

More information

Laddered Multilevel DC/AC Inverters used in Solar Panel Energy Systems

Laddered Multilevel DC/AC Inverters used in Solar Panel Energy Systems Proceedngs of the nd Internatonal Conference on Computer Scence and Electroncs Engneerng (ICCSEE 03) Laddered Multlevel DC/AC Inverters used n Solar Panel Energy Systems Fang Ln Luo, Senor Member IEEE

More information

Simple Interest Loans (Section 5.1) :

Simple Interest Loans (Section 5.1) : Chapter 5 Fnance The frst part of ths revew wll explan the dfferent nterest and nvestment equatons you learned n secton 5.1 through 5.4 of your textbook and go through several examples. The second part

More information

Impact of the design method of permanent magnets synchronous generators for small direct drive wind turbines for battery operation

Impact of the design method of permanent magnets synchronous generators for small direct drive wind turbines for battery operation Impact o the degn method o permanent magnet ynchronou generator or mall drect drve wnd turbne or battery operaton Mha PREDESCU, Dr. eng.*, Aurelan CRǍCIUNESCU, Pro. Dr. **, Andre BEJINARIU, Eng.*, Octavan

More information

Can Auto Liability Insurance Purchases Signal Risk Attitude?

Can Auto Liability Insurance Purchases Signal Risk Attitude? Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159-164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? Chu-Shu L Department of Internatonal Busness, Asa Unversty, Tawan Sheng-Chang

More information

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of

More information

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ). REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

More information

Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application

Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdo-dong,

More information

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika.

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika. VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths user-frendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual

More information

STANDING WAVE TUBE TECHNIQUES FOR MEASURING THE NORMAL INCIDENCE ABSORPTION COEFFICIENT: COMPARISON OF DIFFERENT EXPERIMENTAL SETUPS.

STANDING WAVE TUBE TECHNIQUES FOR MEASURING THE NORMAL INCIDENCE ABSORPTION COEFFICIENT: COMPARISON OF DIFFERENT EXPERIMENTAL SETUPS. STADIG WAVE TUBE TECHIQUES FOR MEASURIG THE ORMAL ICIDECE ABSORPTIO COEFFICIET: COMPARISO OF DIFFERET EXPERIMETAL SETUPS. Angelo Farna (*), Patrzo Faust (**) (*) Dpart. d Ing. Industrale, Unverstà d Parma,

More information

VEHICLE DETECTION BY USING REAR PARTS AND TRACKING SYSTEM

VEHICLE DETECTION BY USING REAR PARTS AND TRACKING SYSTEM IJRET: Internatonal Journal of Research n Engneerng and Technology eissn: 2319-1163 pissn: 2321-7308 VEHICLE DETECTION BY USING REAR PARTS AND TRACKING SYSTEM Yogn Ashokrao Kanhegaonkar 1, Jagtap Rupal

More information

Application of an Improved BP Neural Network Model in Enterprise Network Security Forecasting

Application of an Improved BP Neural Network Model in Enterprise Network Security Forecasting 161 A publcaton of VOL. 46, 15 CHEMICAL ENGINEERING TRANSACTIONS Guest Edtors: Peyu Ren, Yancang L, Hupng Song Copyrght 15, AIDIC Servz S.r.l., ISBN 978-88-9568-37-; ISSN 83-916 The Italan Assocaton of

More information

How To Understand The Results Of The German Meris Cloud And Water Vapour Product

How To Understand The Results Of The German Meris Cloud And Water Vapour Product Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPP-ATBD-ClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller

More information

The issue of whether the Internet will permanently destroy the news media is currently a

The issue of whether the Internet will permanently destroy the news media is currently a Wll the Internet etroy the New Meda? or Can Onlne Advertng Market Save the Meda? by Suan Athey, Emlo Calvano and Johua S. Gan * Frt raft: October, 009 Th Veron: November, 00 PRELIMINARY PLEASE O NOT QUOTE

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

More information

How To Calculate The Accountng Perod Of Nequalty

How To Calculate The Accountng Perod Of Nequalty Inequalty and The Accountng Perod Quentn Wodon and Shlomo Ytzha World Ban and Hebrew Unversty September Abstract Income nequalty typcally declnes wth the length of tme taen nto account for measurement.

More information

Watermark-based Provable Data Possession for Multimedia File in Cloud Storage

Watermark-based Provable Data Possession for Multimedia File in Cloud Storage Vol.48 (CIA 014), pp.103-107 http://dx.do.org/10.1457/astl.014.48.18 Watermar-based Provable Data Possesson for Multmeda Fle n Cloud Storage Yongjun Ren 1,, Jang Xu 1,, Jn Wang 1,, Lmng Fang 3, Jeong-U

More information

A system for real-time calculation and monitoring of energy performance and carbon emissions of RET systems and buildings

A system for real-time calculation and monitoring of energy performance and carbon emissions of RET systems and buildings A system for real-tme calculaton and montorng of energy performance and carbon emssons of RET systems and buldngs Dr PAAIOTIS PHILIMIS Dr ALESSADRO GIUSTI Dr STEPHE GARVI CE Technology Center Democratas

More information

A Performance Analysis of View Maintenance Techniques for Data Warehouses

A Performance Analysis of View Maintenance Techniques for Data Warehouses A Performance Analyss of Vew Mantenance Technques for Data Warehouses Xng Wang Dell Computer Corporaton Round Roc, Texas Le Gruenwald The nversty of Olahoma School of Computer Scence orman, OK 739 Guangtao

More information

21 Vectors: The Cross Product & Torque

21 Vectors: The Cross Product & Torque 21 Vectors: The Cross Product & Torque Do not use our left hand when applng ether the rght-hand rule for the cross product of two vectors dscussed n ths chapter or the rght-hand rule for somethng curl

More information

Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts

Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts Power-of-wo Polces for Sngle- Warehouse Mult-Retaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)

More information

Optical Illusion. Sara Bolouki, Roger Grosse, Honglak Lee, Andrew Ng

Optical Illusion. Sara Bolouki, Roger Grosse, Honglak Lee, Andrew Ng Optical Illuion Sara Bolouki, Roger Groe, Honglak Lee, Andrew Ng. Introduction The goal of thi proect i to explain ome of the illuory phenomena uing pare coding and whitening model. Intead of the pare

More information

s-domain Circuit Analysis

s-domain Circuit Analysis S-Doman naly -Doman rcut naly Tme doman t doman near rcut aplace Tranform omplex frequency doman doman Tranformed rcut Dfferental equaton lacal technque epone waveform aplace Tranform nvere Tranform -

More information

Stochastic Protocol Modeling for Anomaly Based Network Intrusion Detection

Stochastic Protocol Modeling for Anomaly Based Network Intrusion Detection Stochastc Protocol Modelng for Anomaly Based Network Intruson Detecton Juan M. Estevez-Tapador, Pedro Garca-Teodoro, and Jesus E. Daz-Verdejo Department of Electroncs and Computer Technology Unversty of

More information

ESSAYS IN RENEWABLE ENERGY AND EMISSIONS TRADING

ESSAYS IN RENEWABLE ENERGY AND EMISSIONS TRADING ESSAYS IN RENEWABLE ENERGY AND EMISSIONS TRADING By JOSHUA D. KNEIFEL A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE

More information

Report 4668-1b 30.10.2010. Measurement report. Sylomer - field test

Report 4668-1b 30.10.2010. Measurement report. Sylomer - field test Report 4668-1b Meaurement report Sylomer - field tet Report 4668-1b 2(16) Contet 1 Introduction... 3 1.1 Cutomer... 3 1.2 The ite and purpoe of the meaurement... 3 2 Meaurement... 6 2.1 Attenuation of

More information

Fault tolerance in cloud technologies presented as a service

Fault tolerance in cloud technologies presented as a service Internatonal Scentfc Conference Computer Scence 2015 Pavel Dzhunev, PhD student Fault tolerance n cloud technologes presented as a servce INTRODUCTION Improvements n technques for vrtualzaton and performance

More information

1. Measuring association using correlation and regression

1. Measuring association using correlation and regression How to measure assocaton I: Correlaton. 1. Measurng assocaton usng correlaton and regresson We often would lke to know how one varable, such as a mother's weght, s related to another varable, such as a

More information

RequIn, a tool for fast web traffic inference

RequIn, a tool for fast web traffic inference RequIn, a tool for fast web traffc nference Olver aul, Jean Etenne Kba GET/INT, LOR Department 9 rue Charles Fourer 90 Evry, France Olver.aul@nt-evry.fr, Jean-Etenne.Kba@nt-evry.fr Abstract As networked

More information

Measuring adverse selection in managed health care

Measuring adverse selection in managed health care Ž. Journal of Health Economc 19 2000 829 854 www.elever.nlrlocatereconbae Meaurng advere electon n managed health care Rchard G. Frank a,), Jacob Glazer b, Thoma G. McGure c a HarÕard UnÕerty, HarÕard

More information

A Spam Message Filtering Method: focus on run time

A Spam Message Filtering Method: focus on run time , pp.29-33 http://dx.doi.org/10.14257/atl.2014.76.08 A Spam Meage Filtering Method: focu on run time Sin-Eon Kim 1, Jung-Tae Jo 2, Sang-Hyun Choi 3 1 Department of Information Security Management 2 Department

More information

Minimal Coding Network With Combinatorial Structure For Instantaneous Recovery From Edge Failures

Minimal Coding Network With Combinatorial Structure For Instantaneous Recovery From Edge Failures Mnmal Codng Network Wth Combnatoral Structure For Instantaneous Recovery From Edge Falures Ashly Joseph 1, Mr.M.Sadsh Sendl 2, Dr.S.Karthk 3 1 Fnal Year ME CSE Student Department of Computer Scence Engneerng

More information

Multiple-Period Attribution: Residuals and Compounding

Multiple-Period Attribution: Residuals and Compounding Multple-Perod Attrbuton: Resduals and Compoundng Our revewer gave these authors full marks for dealng wth an ssue that performance measurers and vendors often regard as propretary nformaton. In 1994, Dens

More information

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy 4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.

More information

BRNO UNIVERSITY OF TECHNOLOGY

BRNO UNIVERSITY OF TECHNOLOGY BRNO UNIVERSITY OF TECHNOLOGY FACULTY OF INFORMATION TECHNOLOGY DEPARTMENT OF INTELLIGENT SYSTEMS ALGORITHMIC AND MATHEMATICAL PRINCIPLES OF AUTOMATIC NUMBER PLATE RECOGNITION SYSTEMS B.SC. THESIS AUTHOR

More information

A machine vision approach for detecting and inspecting circular parts

A machine vision approach for detecting and inspecting circular parts A machne vson approach for detectng and nspectng crcular parts Du-Mng Tsa Machne Vson Lab. Department of Industral Engneerng and Management Yuan-Ze Unversty, Chung-L, Tawan, R.O.C. E-mal: edmtsa@saturn.yzu.edu.tw

More information

Shielding Equations and Buildup Factors Explained

Shielding Equations and Buildup Factors Explained Sheldng Equatons and uldup Factors Explaned Gamma Exposure Fluence Rate Equatons For an explanaton of the fluence rate equatons used n the unshelded and shelded calculatons, vst ths US Health Physcs Socety

More information

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background: SPEE Recommended Evaluaton Practce #6 efnton of eclne Curve Parameters Background: The producton hstores of ol and gas wells can be analyzed to estmate reserves and future ol and gas producton rates and

More information

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 610-519-4390,

More information