4.5 Signal Flow Graphs

Size: px
Start display at page:

Download "4.5 Signal Flow Graphs"

Transcription

1 3/9/009 4_5 ignl Flow Grphs.doc / 4.5 ignl Flow Grphs Reding Assignment: pp Q: Using individul device scttering prmeters to nlze comple microwve network results in lot of mess mth! Isn t there n esier w? A: Yes! We cn represent microwve network with its signl flow grph. HO: IGNAL FLOW GRAPH Then, we cn decompose this grph using set of stndrd rules. HO: ERIE RULE HO: PARALLEL RULE HO: ELF-LOOP RULE HO: PLITTING RULE It s sort of grphicl w to do lger! Let s do some emples: EXAMPLE: DECOMPOITION OF IGNAL FLOW GRAPH EXAMPLE: IGNAL FLOW GRAPH ANALYI Jim tiles The Univ. of Knss Dept. of EEC

2 3/9/009 4_5 ignl Flow Grphs.doc / ignl Flow grphs cn likewise help us understnd the fundmentl phsicl ehvior of network or device. It cn even help us pproimte the network in w tht mkes it simpler to nlze nd/or design! HO: THE PROPAGATION ERIE Jim tiles The Univ. of Knss Dept. of EEC

3 3/3/009 ignl Flow Grphs / ignl Flow Grphs Consider comple 3-port microwve network, constructed of 5 simpler microwve devices: where n is the scttering mtri of ech device, nd is the overll scttering mtri of the entire 3-port network. Q: Is there n w to determine this overll network scttering mtri from the individul device scttering mtrices? n A: Definitel! Note the wve eiting one port of device is wve entering (i.e., incident on) nother (nd vice vers). This is oundr condition t the port connection etween devices. Jim tiles The Univ. of Knss Dept. of EEC

4 3/3/009 ignl Flow Grphs / Add to this the scttering prmeter equtions from ech individul device, nd we hve sufficient mount of mth to determine the reltionship etween the incident nd eiting wves of the remining three ports in other words, the scttering mtri of the 3-port network! Q: Yikes! Wouldn t tht require lot of tedious lger! A: It sure would! We might use computer to ssist us, or we might use tool emploed since the erl ds of microwve engineering the signl flow grph. ignl flow grphs re helpful in (count em ) three ws! W - ignl flow grphs provide us with grphicl mens of solving lrge sstems of simultneous equtions. W We ll see the signl flow grph cn provide us with rod mp of the wve propgtion pths throughout microwve device or network. If we re ping ttention, we cn glen gret phsicl insight s to the inner working of the microwve device represented the grph. W 3 - ignl flow grphs provide us with quick nd ccurte method for pproimting network or device. We will find tht we cn often replce rther comple grph with much simpler one tht is lmost equivlent. Jim tiles The Univ. of Knss Dept. of EEC

5 3/3/009 ignl Flow Grphs 3/ We find this to e ver helpful when designing microwve components. From the nlsis of these pproimte grphs, we cn often determine design rules or equtions tht re trctle, nd llow us to design components with (ner) optiml performnce. Q: But wht is signl flow grph? A: First, some definitions! Ever signl flow grph consists of set of nodes. These nodes re connected rnches, which re simpl contours with specified direction. Ech rnch likewise hs n ssocited comple vlue. 0.7 j -j Q: Wht could this possil hve to do with microwve engineering? A: Ech port of microwve device is represented two nodes the node nd the node. The node simpl represents the vlue of the normlized mplitude of the wve incident on tht port, evluted t the plne of tht port: Jim tiles The Univ. of Knss Dept. of EEC

6 3/3/009 ignl Flow Grphs 4/ ( = ) V z z n Z + n n np 0n Likewise, the node simpl represents the normlized mplitude of the wve eiting tht port, evluted t the plne of tht port: Vn ( zn = znp ) n Z 0n Note then tht the totl voltge t port is simpl: ( = ) = ( + ) 0 V z z Z n n np n n n The vlue of the rnch connecting two nodes is simpl the vlue of the scttering prmeter relting these two voltge vlues: n + Vn ( zn = znp ) mn V ( z = z ) Z 0n The signl flow grph ove is simpl grphicl representtion of the eqution: m = mn n m m m mp Z 0m Moreover, if multiple rnches enter node, then the voltge represented tht node is the sum of the vlues from ech rnch. For emple, the signl flow grph: Jim tiles The Univ. of Knss Dept. of EEC

7 3/3/009 ignl Flow Grphs 5/ 3 3 is grphicl representtion of the eqution: = Now, consider two-port device with scttering mtri : o tht: = = + = + We cn thus grphicll represent two-port device s: Jim tiles The Univ. of Knss Dept. of EEC

8 3/3/009 ignl Flow Grphs 6/ Now, consider cse where the second port is terminted some lod Γ L : Γ L We now hve et nother eqution: ( = ) = Γ ( = ) V z z V z z + P L P =Γ L Therefore, the signl flow grph of this terminted network is: Γ L Now let s cscde two different two-port networks Γ L Here, the output port of the first device is directl connected to the input port of the second device. We descrie this mthemticll s: Jim tiles The Univ. of Knss Dept. of EEC

9 3/3/009 ignl Flow Grphs 7/ Jim tiles The Univ. of Knss Dept. of EEC = nd = Thus, the signl flow grph of this network is: Q: But wht hppens if the networks re connected with trnsmission lines? A: Recll tht length of trnsmission line with chrcteristic impednce Z 0 is likewise two-port device. Its scttering mtri is: 0 0 j j e e β β = Thus, if the two devices re connected length of trnsmission line: L Γ L Γ 0 Z

10 3/3/009 ignl Flow Grphs 8/ = e = e j β j β so the signl flow grph is: e j β e j β Note tht there is one (nd onl one) independent vrile in this representtion. This independent vrile is node. Γ L This is the onl node of the sfg tht does not hve n incoming rnches. As result, its vlue depends on no other node vlues in the sfg. From the stndpoint of sfg, independent nodes re essentill sources! Of course, this likewise mkes sense phsicll (do ou see wh?). The node vlue represents the comple mplitude of the wve incident on the one-port network. If this vlue is zero, then no power is incident on the network the rest of the nodes (i.e., wve mplitudes) will likewise e zero! Jim tiles The Univ. of Knss Dept. of EEC

11 3/3/009 ignl Flow Grphs 9/ Now, s we wish to determine, for emple:. The reflection coefficient Γ in of the one-port device.. The totl current t port of second network (i.e., network ). 3. The power sored the lod t port of the second () network. In the first cse, we need to determine the vlue of dependent node : Γ in = For the second cse, we must determine the vlue of wve mplitudes nd : I = Z 0 And for the third nd finl cse, the vlues of nodes nd re required: P s = Q: But just how the heck do we determine the vlues of these wve mplitude nodes? Jim tiles The Univ. of Knss Dept. of EEC

12 3/3/009 ignl Flow Grphs 0/ A: One w, of course, is to solve the simultneous equtions tht descrie this network. From network nd network : = + = + = + = + From the trnsmission line: = e = e j β j β And finll from the lod: = Γ L But nother, EVEN BETTER w to determine these vlues is to decompose (reduce) the signl flow grph! Q: Huh? A: ignl flow grph reduction is method for simplifing the comple pths of tht signl flow grph into more direct (ut equivlent!) form. Reduction is rell just grphicl method of decoupling the simultneous equtions tht re descried the sfg. For instnce, in the emple we re considering, the sfg : Jim tiles The Univ. of Knss Dept. of EEC

13 3/3/009 ignl Flow Grphs / e j β e j β Γ L might reduce to: j 8 0. e π j From this grph, we cn directl determine the vlue of ech node (i.e., the vlue of ech wve mplitude), in terms of the one independent vrile. j 0. = 0. = 06. = j 0... j π 8 = 005 = 0e = 03. = 0. And of course, we cn then determine vlues like:. 0. Γ = = = 0. in Jim tiles The Univ. of Knss Dept. of EEC

14 3/3/009 ignl Flow Grphs /. I 8 0. e j π 0 = = Z Z P s ( 03. ) ( 0. ) = = Q: But how do we reduce the sfg to its simplified stte? Just wht is the procedure? A: ignl flow grphs cn e reduced sequentill ppling one of four simple rules. Q: Cn these rules e pplied in n order? A: No! The rules cn onl e pplied when/where the structure of the sfg llows. You must serch the sfg for structures tht llow rule to e pplied, nd the sfg will then e ( little it) reduced. You then serch for the net vlid structure where rule cn e pplied. Eventull, the sfg will e completel reduced! Q:???? A: It s it like solving puzzle. Ever sfg is different, nd so ech will require different reduction procedure. It requires little thought, ut with little prctice, the reduction procedure is esil mstered. You m even find tht it s kind of fun! Jim tiles The Univ. of Knss Dept. of EEC

15 3/3/009 eries Rule / eries Rule Consider these two comple equtions: = α = β where α nd β re ritrr comple constnts. Using the ssocitive propert of multipliction, these two equtions cn comined to form n equivlent set of equtions: ( ) ( ) = α = β = β α = αβ Now let s epress these two sets of equtions s signl flow grphs! The first set provides: α β While the second is: = α = β α αβ = α = αβ Q: He wit! If the two sets of equtions re equivlent, shouldn t the two resulting signl flow grphs likewise e equivlent? Jim tiles The Univ. of Knss Dept. of EEC

16 3/3/009 eries Rule / A: Asolutel! The two signl flow grphs re indeed equivlent. This leds us to our first signl flow grph reduction rule: Rule - eries Rule If node hs one (nd onl one!) incoming rnch, nd one (nd onl one!) outgoing rnch, the node cn e eliminted nd the two rnches cn e comined, with the new rnch hving vlue equl to the product of the originl two. For emple, the grph: 03. j = 03. = j cn e reduced to: 03. j 03. = 03. = j 03. Jim tiles The Univ. of Knss Dept. of EEC

17 3/3/009 Prllel Rule /5 Prllel Rule Consider the comple eqution: = α + β where α nd β re ritrr comple constnts. Using the distriutive propert, the eqution cn equivlentl e epressed s: = α + β ( ) Now let s epress these two equtions s signl flow grphs! The first is: α = α + β β With the second: α + β = ( α + β ) Q: He wit! If the two equtions re equivlent, shouldn t the two resulting signl flow grphs likewise e equivlent? Jim tiles The Univ. of Knss Dept. of EEC

18 3/3/009 Prllel Rule /5 A: Asolutel! The two signl flow grphs re indeed equivlent. This leds us to our second signl flow grph reduction rule: Rule - Prllel Rule If two nodes re connected prllel rnches nd the rnches hve the sme direction the rnches cn e comined into single rnch, with vlue equl to the sum of ech two originl rnches. For emple, the grph: 0. = Cn e reduced to: ( 03 0) =. +. = Jim tiles The Univ. of Knss Dept. of EEC

19 3/3/009 Prllel Rule 3/5 Q: Wht out this signl flow grph? note direction! Cn I rewrite this s: so tht (since =0.): 0.??? A: Asolutel not! NEVER DO THI!! Q: Me I mde mistke. Perhps I should hve rewritten: note direction! Jim tiles The Univ. of Knss Dept. of EEC

20 3/3/009 Prllel Rule 4/5 s this: 5 = 0. so tht (since =5.3): ??? A: Asolutel not! NEVER DO THI EITHER!! From the signl flow grph elow, we cn onl conclude tht = 0.3 nd = Using the series rule (or little it of lger), we cn conclude tht n equivlent signl flow grph to this is: = 0.06 = Q: Yikes! Wht kind of goof rnch egins nd ends t the sme node? Jim tiles The Univ. of Knss Dept. of EEC

21 3/3/009 Prllel Rule 5/5 A: Brnches tht egin nd end t the sme node re clled self-loops. Q: Do these self-loops ctull pper in signl flow grphs? A: Yes, ut the self-loop node will lws hve t lest one other incoming rnch. For emple: = 0.06 j = j 03. Q: But how do we reduce signl flow grph contining self-loop? A: ee rule 3! Jim tiles The Univ. of Knss Dept. of EEC

22 3/3/009 elf Loop Rule /4 elf-loop Rule Now consider the eqution: = α + β + γ A little d of lger llows us to determine the vlue of node : = α + β + γ γ = α + β ( γ) = α + β α β = + γ γ The signl flow grph of the first eqution is: α γ = α + β + γ β Jim tiles The Univ. of Knss Dept. of EEC

23 3/3/009 elf Loop Rule /4 While the signl flow grph of the second is: α β = + γ γ α γ β γ These two signl flow grphs re equivlent! Note the self-loop hs een removed in the second grph. Thus, we now hve method for removing self-loops. This method is rule 3. Rule 3 elf-loop Rule A self-loop cn e eliminte multipling ll of the rnches feeding the self-loop node ( sl ), where sl is the vlue of the self loop rnch. For emple: = j j 04. Jim tiles The Univ. of Knss Dept. of EEC

24 3/3/009 elf Loop Rule 3/4 cn e simplified eliminting the self-loop. We multipl oth of the two rnches feeding the self-loop node : = = sl Therefore: 06. ( 5. ) And thus: j 04. ( 5. ) 075. = j Or nother emple: j = 0.06 j = j 03. Jim tiles The Univ. of Knss Dept. of EEC

25 3/3/009 elf Loop Rule 4/4 ecomes fter reduction using rule 3: = j 0.94 = 0.3 j Q: Wit minute! I think ou forgot something. houldn t ou lso divide the 0.3 rnch vlue 0.06 = 0.94?? A: Nope! The 0.3 rnch is eiting the self-loop node. Onl incoming rnches (e.g., the j rnch) to the selfloop node re modified the self-loop rule! Jim tiles The Univ. of Knss Dept. of EEC

26 3/3/009 plitting Rule /5 plitting Rule Now consider these three equtions: = α = β = γ 3 Using the ssocitive propert, we cn likewise write n equivlent set of equtions: = α = αβ = α 3 The signl flow grph of the first set of equtions is: β α γ While the signl flow grph of the second is: αβ 3 α γ 3 Jim tiles The Univ. of Knss Dept. of EEC

27 3/3/009 plitting Rule /5 Rule 4 plitting Rule If node hs one (nd onl one!) incoming rnch, nd one (or more) eiting rnches, the incoming rnch cn e split, nd directl comined with ech of the eiting rnches. For emple: j = j = 03. = 0. 3 cn e rewritten s: 0. j 03. j 0. 3 = j = j 03. = 0. 3 Jim tiles The Univ. of Knss Dept. of EEC

28 3/3/009 plitting Rule 3/5 Of course, from rule (or from rule 4!), this grph cn e further simplified s: j 03. j j 0. The splitting rule is prticulrl useful when we encounter signl flow grphs of the kind: j = j = j 03. = j 0. j 0. 3 Note this node hs two incoming rnches!! 0. Note this node hs onl one incoming rnch!! We cn split the -0. rnch, nd rewrite the grph s: ( ) j 0. j 0. Note we now hve self-loop, which cn e eliminted using rule #3: j j 0. Jim tiles The Univ. of Knss Dept. of EEC

29 3/3/009 plitting Rule 4/5 Note tht this grph cn e further simplified using rule #. j 094. j 89. j 0. Q: Cn we split the other rnch of the loop? Is this signl flow grph: ( ) j 0. Likewise equivlent to this one??: j 0. j 03. j A: NO!! Do not mke this mistke! We cnnot split the 0.3 rnch ecuse it termintes in node with two incoming rnches (i.e., -j nd 0.3). This is violtion of rule 4. Moreover, the equtions represented the two signl flow grphs re not equivlent the two grphs descrie two different sets of equtions! Jim tiles The Univ. of Knss Dept. of EEC

30 3/3/009 plitting Rule 5/5 It is importnt to rememer tht there is no mgic ehind signl flow grphs. The re simpl grphicl method of representing nd then solving set of liner equtions. As such, the four sic rules of nlzing signl flow grph represent sic lgeric opertions. In fct, signl flow grphs cn e pplied to the nlsis of n liner sstem, not just microwve networks. Jim tiles The Univ. of Knss Dept. of EEC

31 3/3/009 Emple Decomposition of ignl Flow Grph /3 Emple: Decomposition of ignl Flow Grphs Consider the sic -port network, terminted with lod Γ. L Γ L we wnt to determine the vlue: Γ L ( = P ) ( = ) V z z Γ =?? V z z + P In other words, wht is the reflection coefficient of the resulting one-port device? Q: Isn t this simpl? A: Onl if Γ L = 0 (nd it s not)!! o let s decompose (simplif) the signl flow grph nd find out! Jim tiles The Univ. of Knss Dept. of EEC

32 3/3/009 Emple Decomposition of ignl Flow Grph /3 tep : Use rule #4 on node Γ L tep : Use rule #3 on node Γ L Γ L tep 3: And then using rule #: Γ L Γ L Γ L Γ L Γ L Γ L Jim tiles The Univ. of Knss Dept. of EEC

33 3/3/009 Emple Decomposition of ignl Flow Grph 3/3 tep 4: Use rule on nodes nd Γ L + Γ ΓL L ΓL ΓL Therefore: Γ = = Γ + Γ L L Note if Γ = 0, then L =! Jim tiles The Univ. of Knss Dept. of EEC

34 3/5/009 Emple ignl Flow Grph Anlsis /6 Emple: Anlsis Using ignl Flow Grphs Below is single-port device (with input t port ) constructed with two two-port devices ( nd ), qurter wvelength trnsmission line, nd lod impednce. j = λ 4 Z 0 Z 0 Γ L = port (input) port port port Where Z 0 = 50Ω. The scttering mtrices of the two-port devices re: = = Likewise, we know tht the vlue of the voltge wve incident on port of device is: ( = ) + V0 z zp j j = = Z V Jim tiles The Univ. of Knss Dept. of EEC

35 3/5/009 Emple ignl Flow Grph Anlsis /6 Now, let s drw the complete signl flow grph of this circuit, nd then reduce the grph to determine: ) The totl current through lod Γ L. ) The power delivered to (i.e., sored ) port. The signl flow grph descriing this network is: e j β e j β Γ L Inserting the numeric vlues of rnches: = j 5 j j 08. Jim tiles The Univ. of Knss Dept. of EEC

36 3/5/009 Emple ignl Flow Grph Anlsis 3/6 Removing the zero vlued rnches: = j 5 j j And now ppling splitting rule 4: 08. = j 5 j j Followed the self-loop rule 3: = j 5 j ( ) 04. = = j 08. Jim tiles The Univ. of Knss Dept. of EEC

37 3/5/009 Emple ignl Flow Grph Anlsis 4/6 Now, let s used this simplified signl flow grph to find the solutions to our questions! ) The totl current through lod Γ L. The totl current through the lod is: ( ) + ( = P ) ( = P ) I = I z = z L P V0 z z V0 z z = Z0 = Z0 = 50 Thus, we need to determine the vlue of nodes nd. Using the series rule on our signl flow grph: = j j j 04. From this grph we cn conclude: Note we ve simpl ignored (i.e., neglected to plot) the node for which we hve no interest! Jim tiles The Univ. of Knss Dept. of EEC

38 3/5/009 Emple ignl Flow Grph Anlsis 5/6 nd: j j j = = = 0. 5 ( ) = = 0. = 0 Therefore: ( ) I L = = = = 0 0. ma ) The power delivered to (i.e., sored ) port. The power delivered to port is: P = P P s + ( = ) ( = ) + P P V z z V z z = Z Z 0 0 = Thus, we need determine the vlues of nodes nd. Agin using the series rule on our signl flow grph: 035. = j 5 0. Agin we ve simpl ignored (i.e., neglected to plot) the node for which we hve no interest! Jim tiles The Univ. of Knss Dept. of EEC

39 3/5/009 Emple ignl Flow Grph Anlsis 6/6 And then using the prllel rule : = j 5 = Therefore: ( 5 ) = = j = j 0 nd: j 5 j P s = = = mw Jim tiles The Univ. of Knss Dept. of EEC

40 3/9/009 The Propgtion eries.doc /8 The Propgtion eries Q: You erlier stted tht signl flow grphs re helpful in (count em ) three ws. I now understnd the first w: W - ignl flow grphs provide us with grphicl mens of solving lrge sstems of simultneous equtions. But wht out ws nd 3?? W We ll see the signl flow grph cn provide us with rod mp of the wve propgtion pths throughout microwve device or network. W 3 - ignl flow grphs provide us with quick nd ccurte method for pproimting network or device. A: Consider the sfg elow: j j Jim tiles The Univ. of Knss Dept. of EEC

41 3/9/009 The Propgtion eries.doc /8 Note tht node is the onl independent node. This signl flow grph is for rther comple single-port (port ) device. we wish to determine the wve mplitude eiting port. In other words, we seek: = Γ in Using our four reduction rules, the signl flow grph ove is simplified to: j 3 4 j j 036. j Q: He, node is not connected to nthing. Wht does this men? A: It mens tht = 0 regrdless of the vlue of incident wve. I.E.,: Γ in = = 0 In other words, port is mtched lod! Q: But look t the originl signl flow grph; it doesn t look like mtched lod. How cn the eiting wve t port e zero? Jim tiles The Univ. of Knss Dept. of EEC

42 3/9/009 The Propgtion eries.doc 3/8 A: A signl flow grph provides it of propgtion rod mp through the device or network. It llows us to understnd often in ver phsicl w the propgtion of n incident wve once it enters device. We ccomplish this identifing from the sfg propgtion pths from n independent node to some other node (e.g., n eiting node). These pths re simpl sequence of rnches (pointing in the correct direction!) tht led from the independent node to this other node. Ech pth hs vlue tht is equl to the product of ech rnch of the pth. Perhps this is est eplined with some emples. One pth etween independent (incident wve) node nd (eiting wve) node is shown elow: 08. j j We ll ritrril cll this pth, nd its vlue: ( ) ( ) ( ) p = 0.5 j 0.4 j 0.5 = 0. Jim tiles The Univ. of Knss Dept. of EEC

43 3/9/009 The Propgtion eries.doc 4/8 Another propgtion pth (pth 5, s) is: 08. j j ( 0.5) ( 0.4) ( 0.35) ( 0.8)( 0.5)( 0.8) ( 0.5) p = j j j j = j 4 ( 0.35)( 0.4)( 0.8) ( 0.5) = 0.0 Q: Wh re we doing this? 3 A: The eiting wve t port (wve mplitude ) is simpl the superposition of ll the propgtion pths from incident node! Mthemticll speking: = p Γ = = p n n in n n Q: Won t there e n wful lot of propgtion pths? A: Yes! As mtter of fct there re n infinite numer of pths tht connect node nd. Therefore: = p Γ = = p n n in n n Jim tiles The Univ. of Knss Dept. of EEC

44 3/9/009 The Propgtion eries.doc 5/8 Q: Yikes! Does this infinite series converge? A: Note tht the series represents finite phsicl vlue (e.g., Γ in ), so tht the infinite series must converge to the correct finite vlue. Q: In this emple we found tht Γ in = 0. This mens tht the infinite propgtion series is likewise zero: Γ = p = in n n 0 Do we conclude from this tht ll propgtion pths re zero: p = 0????? n A: Asolutel not! Rememer, we hve lred determined tht p = 0. nd p 4 = 0.0 definitel not zero-vlued! In fct for this emple, none of the propgtion pths p n re precisel equl to zero! Q: But then wh is: pn = 0??? n A: Rememer, the pth vlues n p re comple. A sum of nonzero comple vlues cn equl zero (s it pprentl does in this cse!). Jim tiles The Univ. of Knss Dept. of EEC

45 3/9/009 The Propgtion eries.doc 6/8 Thus, perfectl rtionl w of viewing this network is to conclude tht there re n infinite numer of non-zero wves eiting port : Γ = p where p 0 in n n n It just so hppens tht these wves coherentl dd together to zero: Γ = p = 0 in n n the essentill cncel ech other out! Q: o, I now pprecite the fct tht signl flow grphs: ) provides grphicl method for solving liner equtions nd ) lso provides method for phsicll evluting the wve propgtion pths through network/device. But wht out helpful W 3: W 3 - ignl flow grphs provide us with quick nd ccurte method for pproimting network or device.?? A: The propgtion series of microwve network is ver nlogous to Tlor eries epnsion: n d f( ) f ( ) = ( ) n d n = 0 = n Jim tiles The Univ. of Knss Dept. of EEC

46 3/9/009 The Propgtion eries.doc 7/8 Note tht there likewise is infinite numer of terms, et the Tlor eries is quite helpful in engineering. Often, we engineers simpl truncte this infinite series, mking it finite one: N n d f( ) f ( ) ( ) n d n = 0 = Q: Yikes! Doesn t this result in error? n A: Asolutel! The truncted series is n pproimtion. We hve less error if more terms re retined; more error if fewer terms re retined. The trick is to retin the significnt terms of the infinite series, nd truncte those less importnt insignificnt terms. In this w, we seek to form n ccurte pproimtion, using the fewest numer of terms. Q: But how do we know which terms re significnt, nd which re not? A: For Tlor eries, we find tht s the order n increses, the significnce of the term generll (ut not lws!) decreses. Q: But wht out our propgtion series? How cn we determine which pths re significnt in the series? Jim tiles The Univ. of Knss Dept. of EEC

47 3/9/009 The Propgtion eries.doc 8/8 A: Almost lws, the most significnt pths in propgtion series re the forwrd pths of signl flow grph. forwrd pth \ˈfoṙ wərdˈ päth\ noun A pth through signl flow grph tht psses through n given node no more thn once. A pth tht psses through n node two times (or more) is therefore not forwrd pth. In our emple, pth is forwrd pth. It psses through four nodes s it trvels from node to node, ut it psses through ech of these nodes onl once: 08. j j Alterntivel, pth 5 is not forwrd pth: 08. j j Jim tiles The Univ. of Knss Dept. of EEC

48 3/9/009 The Propgtion eries.doc 9/8 We see tht pth 5 psses through si different nodes s it trvels from node to node. However, it twice psses through four of these nodes. The good news out forwrd pths is tht there re lws finite numer of them. Agin, these pths re tpicll the most significnt in the propgtion series, so we cn determine n pproimte vlue for sfg nodes considering onl these forwrd pths in the propgtion series: N pn n n= p fp n fp where p n represents the vlue of one of the N forwrd pths. Q: Is pth the onl forwrd pth in our emple sfg? A: No, there re three. Pth is the most direct: p = j j Of course we lred hve identified pth : Jim tiles The Univ. of Knss Dept. of EEC

49 3/9/009 The Propgtion eries.doc 0/8 p = j j And finll, pth 3 is the longest forwrd pth: 3 ( 0.5) ( 0.8)( 0.5)( 0.8) ( 0.5) 3 j ( 0.8) ( 0.5) p = j j = = 0.08 j j Thus, n pproimte vlue of Γin is: Γ in = 3 n = p fp n = p + p + p 3 = = Jim tiles The Univ. of Knss Dept. of EEC

50 3/9/009 The Propgtion eries.doc /8 Q: He wit! We determined erlier tht Γ in = 0, ut now our sing tht Γ in = Which is correct?? A: The correct nswer is Γ in = 0. It ws determined using the four sfg reduction rules no pproimtions were involved! Conversel, the vlue Γ in = ws determined using truncted form of the propgtion series the series ws limited to just the three most significnt terms (i.e., the forwrd pths). The result is esier to otin, ut it is just n pproimtion (the nswers will contin error!). For emple, consider the reduced signl flow grph (no pproimtion error): 04. j j 03. Ect FG 088. j j 06. Compre this to the sme sfg, computed using onl the forwrd pths: j j 04. Appro. FG 036. j 036. j Jim tiles The Univ. of Knss Dept. of EEC

51 3/9/009 The Propgtion eries.doc /8 No surprise, the pproimte sfg (using forwrd pths onl) is not the sme s the ect sfg (using reduction rules). The pproimte sfg contins error, ut note this error is not too d. The vlues of the pproimte sfg re certinl close to tht of the ect sfg. Q: Is there n w to improve the ccurc of this pproimtion? A: Certinl. The error is result of truncting the infinite propgtion series. Note we severel truncted the series out of n infinite numer of terms, we retined onl three (the forwrd pths). If we retin more terms, we will likel get more ccurte nswer. Q: o wh did these pproimte nswers turn out so well, given tht we onl used three terms? A: We retined the three most significnt terms, we will find tht the forwrd pths tpicll hve the lrgest mgnitudes of ll propgtion pths. Q: An ide wht the net most significnt terms re? A: Yup. The forwrd pths re ll those propgtion pths tht pss through n node no more thn one time. The net most significnt pths re lmost certinl those pths tht pss through n node no more thn two times. Jim tiles The Univ. of Knss Dept. of EEC

52 3/9/009 The Propgtion eries.doc 3/8 Pth 4 is n emple of such pth: 08. j j There re three more of these pths (pssing through node no more thn two times) see if ou cn find them! After determining the vlues for these pths, we cn dd 4 more terms to our summtion (now we hve seven terms!): Γ in = 7 n = p n ( p p p3) ( p4 p5 p6 p7) ( 0.036) ( ) = = = Note this vlue is closer to the correct vlue of zero thn ws our previous (using onl three terms) nswer of As we dd more terms to the summtion, this pproimte nswer will get closer nd closer to the correct vlue of zero. However, it will e ectl zero (to n infinite numer of deciml points) onl if we sum n infinite numer of terms! Jim tiles The Univ. of Knss Dept. of EEC

53 3/9/009 The Propgtion eries.doc 4/8 Q: The significnce of given pth seem to e inversel proportionl to the numer of times it psses through n node. Is this true? If so, then wh is it true? A: It is true (generll speking)! A propgtion pth tht trvels though node ten times is much less likel to e significnt to the propgtion series (i.e., summtion) thn pth tht psses through n node no more thn (s) four times. The reson for this is tht the significnce of given term in summtion is dependent on its mgnitude (i.e., p n ). If the mgnitude of term is smll, it will hve fr less ffect (i.e., significnce) on the sum thn will term whose mgnitude is lrge. Q: You seem to e sing tht pths trveling through fewer nodes hve lrger mgnitudes thn those trveling through mn nodes. Is tht true? If so wh? A: Keep in mind tht microwve sfg reltes wve mplitudes. The rnch vlues re therefore lws scttering prmeters. One importnt thing out scttering prmeters, their mgnitudes (for pssive devices) re lws less thn or equl to one! mn Jim tiles The Univ. of Knss Dept. of EEC

54 3/9/009 The Propgtion eries.doc 5/8 Recll the vlue of pth is simpl the product of ech rnch tht forms the pth. The more rnches (nd thus nodes), the more terms in this product. ince ech term hs mgnitude less thn one, the mgnitude of product of mn terms is much smller thn product of few terms. For emple: 3 j 0.7 = nd 0 j 0.7 = 0.08 In other words, pths with more rnches (i.e., more nodes) will tpicll hve smller mgnitudes nd so re less significnt in the propgtion series. Note pth in our emple trveled long one rnch onl: p = 0.44 Pth hs five rnches: p = 0. Pth 3 seven rnches: p 3 = 0.08 Pth 4 nine rnches: p 4 = 0.04 Jim tiles The Univ. of Knss Dept. of EEC

55 3/9/009 The Propgtion eries.doc 6/8 Pth 5 eleven rnches: p 5 = 0.0 Pth 6 eleven rnches: p 6 = 0.0 Pth 7 thirteen rnches: p 7 = Hopefull it is evident tht the mgnitude diminishes s the pth length increses. Q: o, does this men tht we should ndon our four reduction rules, nd insted use truncted propgtion series to evlute signl flow grphs?? A: Asolutel not! Rememer, truncting the propgtion series lws results in some error. This error might e sufficientl smll if we retin enough terms, ut knowing precisel how mn terms to retin is prolemtic. We find tht in most cses it is simpl not worth the effort use the four reduction rules insted (it s not like the re prticulrl difficult!). Jim tiles The Univ. of Knss Dept. of EEC

56 3/9/009 The Propgtion eries.doc 7/8 Q: You s tht in most cses it is not worth the effort. Are there some cses where this pproimtion is ctull useful?? A: Yes. A truncted propgtion series (tpicll using onl the forwrd pths) is used when these three things re true:. The network or device is comple (lots of nodes nd rnches).. We cn conclude from our knowledge of the device tht the forwrd pths re sufficient for n ccurte pproimtion (i.e., the mgnitudes of ll other pths in the series re lmost certinl ver smll). 3. The rnch vlues re not numeric, ut insted re vriles tht re dependent on the phsicl prmeters of the device (e.g., chrcteristic impednce or line length). The result is tpicll trctle mthemticl eqution tht reltes the design vriles (e.g., Z 0 or ) of comple device to specific device prmeter. For emple, we might use truncted propgtion series to pproimtel determine some function: (,,, ) Γin Z Z 0 0 Jim tiles The Univ. of Knss Dept. of EEC

57 3/9/009 The Propgtion eries.doc 8/8 If we desire mtched input (i.e., ( ) Γ in Z,, Z, = 0) we 0 0 cn solve this trctle design eqution for the (nerl) proper vlues of Z0,, Z0,. We will use this technique to gret effect for designing multi-section mtching networks nd multi-section coupled line couplers. e e j θ j θ e e j θ j θ sin j jc θ e θ sin j jc θ e θ sin j jc3 θ e θ sin j jc θ e θ sin j jc θ e θ sin j jc3 θ e θ e e j θ j θ 3 3 e j θ j jc sinθ e θ sin j jc θ e θ e j θ e j θ sin j jc θ e θ sin j jc θ e θ e j θ e j θ sin j jc3 θ e θ sin j jc3 θ e θ e j θ 4 4 The signl flow grph of three-section coupled-line coupler. Jim tiles The Univ. of Knss Dept. of EEC

Or more simply put, when adding or subtracting quantities, their uncertainties add.

Or more simply put, when adding or subtracting quantities, their uncertainties add. Propgtion of Uncertint through Mthemticl Opertions Since the untit of interest in n eperiment is rrel otined mesuring tht untit directl, we must understnd how error propgtes when mthemticl opertions re

More information

Reasoning to Solve Equations and Inequalities

Reasoning to Solve Equations and Inequalities Lesson4 Resoning to Solve Equtions nd Inequlities In erlier work in this unit, you modeled situtions with severl vriles nd equtions. For exmple, suppose you were given usiness plns for concert showing

More information

Multiplication and Division - Left to Right. Addition and Subtraction - Left to Right.

Multiplication and Division - Left to Right. Addition and Subtraction - Left to Right. Order of Opertions r of Opertions Alger P lese Prenthesis - Do ll grouped opertions first. E cuse Eponents - Second M D er Multipliction nd Division - Left to Right. A unt S hniqu Addition nd Sutrction

More information

EQUATIONS OF LINES AND PLANES

EQUATIONS OF LINES AND PLANES EQUATIONS OF LINES AND PLANES MATH 195, SECTION 59 (VIPUL NAIK) Corresponding mteril in the ook: Section 12.5. Wht students should definitely get: Prmetric eqution of line given in point-direction nd twopoint

More information

P.3 Polynomials and Factoring. P.3 an 1. Polynomial STUDY TIP. Example 1 Writing Polynomials in Standard Form. What you should learn

P.3 Polynomials and Factoring. P.3 an 1. Polynomial STUDY TIP. Example 1 Writing Polynomials in Standard Form. What you should learn 33337_0P03.qp 2/27/06 24 9:3 AM Chpter P Pge 24 Prerequisites P.3 Polynomils nd Fctoring Wht you should lern Polynomils An lgeric epression is collection of vriles nd rel numers. The most common type of

More information

Section 7-4 Translation of Axes

Section 7-4 Translation of Axes 62 7 ADDITIONAL TOPICS IN ANALYTIC GEOMETRY Section 7-4 Trnsltion of Aes Trnsltion of Aes Stndrd Equtions of Trnslted Conics Grphing Equtions of the Form A 2 C 2 D E F 0 Finding Equtions of Conics In the

More information

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( )

Polynomial Functions. Polynomial functions in one variable can be written in expanded form as ( ) Polynomil Functions Polynomil functions in one vrible cn be written in expnded form s n n 1 n 2 2 f x = x + x + x + + x + x+ n n 1 n 2 2 1 0 Exmples of polynomils in expnded form re nd 3 8 7 4 = 5 4 +

More information

2 DIODE CLIPPING and CLAMPING CIRCUITS

2 DIODE CLIPPING and CLAMPING CIRCUITS 2 DIODE CLIPPING nd CLAMPING CIRCUITS 2.1 Ojectives Understnding the operting principle of diode clipping circuit Understnding the operting principle of clmping circuit Understnding the wveform chnge of

More information

Appendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered:

Appendix D: Completing the Square and the Quadratic Formula. In Appendix A, two special cases of expanding brackets were considered: Appendi D: Completing the Squre nd the Qudrtic Formul Fctoring qudrtic epressions such s: + 6 + 8 ws one of the topics introduced in Appendi C. Fctoring qudrtic epressions is useful skill tht cn help you

More information

Unit 6: Exponents and Radicals

Unit 6: Exponents and Radicals Eponents nd Rdicls -: The Rel Numer Sstem Unit : Eponents nd Rdicls Pure Mth 0 Notes Nturl Numers (N): - counting numers. {,,,,, } Whole Numers (W): - counting numers with 0. {0,,,,,, } Integers (I): -

More information

Answer, Key Homework 10 David McIntyre 1

Answer, Key Homework 10 David McIntyre 1 Answer, Key Homework 10 Dvid McIntyre 1 This print-out should hve 22 questions, check tht it is complete. Multiple-choice questions my continue on the next column or pge: find ll choices efore mking your

More information

Graphs on Logarithmic and Semilogarithmic Paper

Graphs on Logarithmic and Semilogarithmic Paper 0CH_PHClter_TMSETE_ 3//00 :3 PM Pge Grphs on Logrithmic nd Semilogrithmic Pper OBJECTIVES When ou hve completed this chpter, ou should be ble to: Mke grphs on logrithmic nd semilogrithmic pper. Grph empiricl

More information

Lecture 9 Microwave Network Analysis A. Nassiri - ANL June 19, 2003. Microwave Physics and Techniques UCSB June 2003 1

Lecture 9 Microwave Network Analysis A. Nassiri - ANL June 19, 2003. Microwave Physics and Techniques UCSB June 2003 1 Lecture 9 Microwve Network nlysis. Nssiri - NL June 9, 003 Microwve Physics nd Techniques UC June 003 -Prmeter Mesurement Technique VVM: The vector voltmeter mesures the mgnitude of reference nd test voltge

More information

Algebra Review. How well do you remember your algebra?

Algebra Review. How well do you remember your algebra? Algebr Review How well do you remember your lgebr? 1 The Order of Opertions Wht do we men when we write + 4? If we multiply we get 6 nd dding 4 gives 10. But, if we dd + 4 = 7 first, then multiply by then

More information

Math 135 Circles and Completing the Square Examples

Math 135 Circles and Completing the Square Examples Mth 135 Circles nd Completing the Squre Exmples A perfect squre is number such tht = b 2 for some rel number b. Some exmples of perfect squres re 4 = 2 2, 16 = 4 2, 169 = 13 2. We wish to hve method for

More information

CS99S Laboratory 2 Preparation Copyright W. J. Dally 2001 October 1, 2001

CS99S Laboratory 2 Preparation Copyright W. J. Dally 2001 October 1, 2001 CS99S Lortory 2 Preprtion Copyright W. J. Dlly 2 Octoer, 2 Ojectives:. Understnd the principle of sttic CMOS gte circuits 2. Build simple logic gtes from MOS trnsistors 3. Evlute these gtes to oserve logic

More information

Introduction to Integration Part 2: The Definite Integral

Introduction to Integration Part 2: The Definite Integral Mthemtics Lerning Centre Introduction to Integrtion Prt : The Definite Integrl Mr Brnes c 999 Universit of Sdne Contents Introduction. Objectives...... Finding Ares 3 Ares Under Curves 4 3. Wht is the

More information

Pure C4. Revision Notes

Pure C4. Revision Notes Pure C4 Revision Notes Mrch 0 Contents Core 4 Alger Prtil frctions Coordinte Geometry 5 Prmetric equtions 5 Conversion from prmetric to Crtesin form 6 Are under curve given prmetriclly 7 Sequences nd

More information

Factoring Polynomials

Factoring Polynomials Fctoring Polynomils Some definitions (not necessrily ll for secondry school mthemtics): A polynomil is the sum of one or more terms, in which ech term consists of product of constnt nd one or more vribles

More information

Lectures 8 and 9 1 Rectangular waveguides

Lectures 8 and 9 1 Rectangular waveguides 1 Lectures 8 nd 9 1 Rectngulr wveguides y b x z Consider rectngulr wveguide with 0 < x b. There re two types of wves in hollow wveguide with only one conductor; Trnsverse electric wves

More information

Bayesian Updating with Continuous Priors Class 13, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom

Bayesian Updating with Continuous Priors Class 13, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom Byesin Updting with Continuous Priors Clss 3, 8.05, Spring 04 Jeremy Orloff nd Jonthn Bloom Lerning Gols. Understnd prmeterized fmily of distriutions s representing continuous rnge of hypotheses for the

More information

LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES

LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES LINEAR TRANSFORMATIONS AND THEIR REPRESENTING MATRICES DAVID WEBB CONTENTS Liner trnsformtions 2 The representing mtrix of liner trnsformtion 3 3 An ppliction: reflections in the plne 6 4 The lgebr of

More information

PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY

PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY MAT 0630 INTERNET RESOURCES, REVIEW OF CONCEPTS AND COMMON MISTAKES PROF. BOYAN KOSTADINOV NEW YORK CITY COLLEGE OF TECHNOLOGY, CUNY Contents 1. ACT Compss Prctice Tests 1 2. Common Mistkes 2 3. Distributive

More information

PHY 222 Lab 8 MOTION OF ELECTRONS IN ELECTRIC AND MAGNETIC FIELDS

PHY 222 Lab 8 MOTION OF ELECTRONS IN ELECTRIC AND MAGNETIC FIELDS PHY 222 Lb 8 MOTION OF ELECTRONS IN ELECTRIC AND MAGNETIC FIELDS Nme: Prtners: INTRODUCTION Before coming to lb, plese red this pcket nd do the prelb on pge 13 of this hndout. From previous experiments,

More information

Integration. 148 Chapter 7 Integration

Integration. 148 Chapter 7 Integration 48 Chpter 7 Integrtion 7 Integrtion t ech, by supposing tht during ech tenth of second the object is going t constnt speed Since the object initilly hs speed, we gin suppose it mintins this speed, but

More information

MA 15800 Lesson 16 Notes Summer 2016 Properties of Logarithms. Remember: A logarithm is an exponent! It behaves like an exponent!

MA 15800 Lesson 16 Notes Summer 2016 Properties of Logarithms. Remember: A logarithm is an exponent! It behaves like an exponent! MA 5800 Lesson 6 otes Summer 06 Rememer: A logrithm is n eponent! It ehves like n eponent! In the lst lesson, we discussed four properties of logrithms. ) log 0 ) log ) log log 4) This lesson covers more

More information

Regular Sets and Expressions

Regular Sets and Expressions Regulr Sets nd Expressions Finite utomt re importnt in science, mthemtics, nd engineering. Engineers like them ecuse they re super models for circuits (And, since the dvent of VLSI systems sometimes finite

More information

A.7.1 Trigonometric interpretation of dot product... 324. A.7.2 Geometric interpretation of dot product... 324

A.7.1 Trigonometric interpretation of dot product... 324. A.7.2 Geometric interpretation of dot product... 324 A P P E N D I X A Vectors CONTENTS A.1 Scling vector................................................ 321 A.2 Unit or Direction vectors...................................... 321 A.3 Vector ddition.................................................

More information

Pentominoes. Pentominoes. Bruce Baguley Cascade Math Systems, LLC. The pentominoes are a simple-looking set of objects through which some powerful

Pentominoes. Pentominoes. Bruce Baguley Cascade Math Systems, LLC. The pentominoes are a simple-looking set of objects through which some powerful Pentominoes Bruce Bguley Cscde Mth Systems, LLC Astrct. Pentominoes nd their reltives the polyominoes, polycues, nd polyhypercues will e used to explore nd pply vrious importnt mthemticl concepts. In this

More information

Example 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers.

Example 27.1 Draw a Venn diagram to show the relationship between counting numbers, whole numbers, integers, and rational numbers. 2 Rtionl Numbers Integers such s 5 were importnt when solving the eqution x+5 = 0. In similr wy, frctions re importnt for solving equtions like 2x = 1. Wht bout equtions like 2x + 1 = 0? Equtions of this

More information

Operations with Polynomials

Operations with Polynomials 38 Chpter P Prerequisites P.4 Opertions with Polynomils Wht you should lern: Write polynomils in stndrd form nd identify the leding coefficients nd degrees of polynomils Add nd subtrct polynomils Multiply

More information

AREA OF A SURFACE OF REVOLUTION

AREA OF A SURFACE OF REVOLUTION AREA OF A SURFACE OF REVOLUTION h cut r πr h A surfce of revolution is formed when curve is rotted bout line. Such surfce is the lterl boundr of solid of revolution of the tpe discussed in Sections 7.

More information

Section 5-4 Trigonometric Functions

Section 5-4 Trigonometric Functions 5- Trigonometric Functions Section 5- Trigonometric Functions Definition of the Trigonometric Functions Clcultor Evlution of Trigonometric Functions Definition of the Trigonometric Functions Alternte Form

More information

5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one.

5.2. LINE INTEGRALS 265. Let us quickly review the kind of integrals we have studied so far before we introduce a new one. 5.2. LINE INTEGRALS 265 5.2 Line Integrls 5.2.1 Introduction Let us quickly review the kind of integrls we hve studied so fr before we introduce new one. 1. Definite integrl. Given continuous rel-vlued

More information

LECTURE #05. Learning Objective. To describe the geometry in and around a unit cell in terms of directions and planes.

LECTURE #05. Learning Objective. To describe the geometry in and around a unit cell in terms of directions and planes. LECTURE #05 Chpter 3: Lttice Positions, Directions nd Plnes Lerning Objective To describe the geometr in nd round unit cell in terms of directions nd plnes. 1 Relevnt Reding for this Lecture... Pges 64-83.

More information

The Velocity Factor of an Insulated Two-Wire Transmission Line

The Velocity Factor of an Insulated Two-Wire Transmission Line The Velocity Fctor of n Insulted Two-Wire Trnsmission Line Problem Kirk T. McDonld Joseph Henry Lbortories, Princeton University, Princeton, NJ 08544 Mrch 7, 008 Estimte the velocity fctor F = v/c nd the

More information

SPECIAL PRODUCTS AND FACTORIZATION

SPECIAL PRODUCTS AND FACTORIZATION MODULE - Specil Products nd Fctoriztion 4 SPECIAL PRODUCTS AND FACTORIZATION In n erlier lesson you hve lernt multipliction of lgebric epressions, prticulrly polynomils. In the study of lgebr, we come

More information

www.mathsbox.org.uk e.g. f(x) = x domain x 0 (cannot find the square root of negative values)

www.mathsbox.org.uk e.g. f(x) = x domain x 0 (cannot find the square root of negative values) www.mthsbo.org.uk CORE SUMMARY NOTES Functions A function is rule which genertes ectl ONE OUTPUT for EVERY INPUT. To be defined full the function hs RULE tells ou how to clculte the output from the input

More information

Integration by Substitution

Integration by Substitution Integrtion by Substitution Dr. Philippe B. Lvl Kennesw Stte University August, 8 Abstrct This hndout contins mteril on very importnt integrtion method clled integrtion by substitution. Substitution is

More information

1. Find the zeros Find roots. Set function = 0, factor or use quadratic equation if quadratic, graph to find zeros on calculator

1. Find the zeros Find roots. Set function = 0, factor or use quadratic equation if quadratic, graph to find zeros on calculator AP Clculus Finl Review Sheet When you see the words. This is wht you think of doing. Find the zeros Find roots. Set function =, fctor or use qudrtic eqution if qudrtic, grph to find zeros on clcultor.

More information

Use Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions.

Use Geometry Expressions to create a more complex locus of points. Find evidence for equivalence using Geometry Expressions. Lerning Objectives Loci nd Conics Lesson 3: The Ellipse Level: Preclculus Time required: 120 minutes In this lesson, students will generlize their knowledge of the circle to the ellipse. The prmetric nd

More information

Warm-up for Differential Calculus

Warm-up for Differential Calculus Summer Assignment Wrm-up for Differentil Clculus Who should complete this pcket? Students who hve completed Functions or Honors Functions nd will be tking Differentil Clculus in the fll of 015. Due Dte:

More information

, and the number of electrons is -19. e e 1.60 10 C. The negatively charged electrons move in the direction opposite to the conventional current flow.

, and the number of electrons is -19. e e 1.60 10 C. The negatively charged electrons move in the direction opposite to the conventional current flow. Prolem 1. f current of 80.0 ma exists in metl wire, how mny electrons flow pst given cross section of the wire in 10.0 min? Sketch the directions of the current nd the electrons motion. Solution: The chrge

More information

Increasing Q of Waveguide Pulse-Compression Cavities

Increasing Q of Waveguide Pulse-Compression Cavities Circuit nd Electromgnetic System Design Notes Note 61 3 July 009 Incresing Q of Wveguide Pulse-Compression Cvities Crl E. Bum University of New Mexico Deprtment of Electricl nd Computer Engineering Albuquerque

More information

Quick Guide to Lisp Implementation

Quick Guide to Lisp Implementation isp Implementtion Hndout Pge 1 o 10 Quik Guide to isp Implementtion Representtion o si dt strutures isp dt strutures re lled S-epressions. The representtion o n S-epression n e roken into two piees, the

More information

Homework 3 Solutions

Homework 3 Solutions CS 341: Foundtions of Computer Science II Prof. Mrvin Nkym Homework 3 Solutions 1. Give NFAs with the specified numer of sttes recognizing ech of the following lnguges. In ll cses, the lphet is Σ = {,1}.

More information

Summary: Vectors. This theorem is used to find any points (or position vectors) on a given line (direction vector). Two ways RT can be applied:

Summary: Vectors. This theorem is used to find any points (or position vectors) on a given line (direction vector). Two ways RT can be applied: Summ: Vectos ) Rtio Theoem (RT) This theoem is used to find n points (o position vectos) on given line (diection vecto). Two ws RT cn e pplied: Cse : If the point lies BETWEEN two known position vectos

More information

Understanding Basic Analog Ideal Op Amps

Understanding Basic Analog Ideal Op Amps Appliction Report SLAA068A - April 2000 Understnding Bsic Anlog Idel Op Amps Ron Mncini Mixed Signl Products ABSTRACT This ppliction report develops the equtions for the idel opertionl mplifier (op mp).

More information

COMPLEX FRACTIONS. section. Simplifying Complex Fractions

COMPLEX FRACTIONS. section. Simplifying Complex Fractions 58 (6-6) Chpter 6 Rtionl Epressions undles tht they cn ttch while working together for 0 hours. 00 600 6 FIGURE FOR EXERCISE 9 95. Selling. George sells one gzine suscription every 0 inutes, wheres Theres

More information

Exponential and Logarithmic Functions

Exponential and Logarithmic Functions Nme Chpter Eponentil nd Logrithmic Functions Section. Eponentil Functions nd Their Grphs Objective: In this lesson ou lerned how to recognize, evlute, nd grph eponentil functions. Importnt Vocbulr Define

More information

9 CONTINUOUS DISTRIBUTIONS

9 CONTINUOUS DISTRIBUTIONS 9 CONTINUOUS DISTIBUTIONS A rndom vrible whose vlue my fll nywhere in rnge of vlues is continuous rndom vrible nd will be ssocited with some continuous distribution. Continuous distributions re to discrete

More information

Econ 4721 Money and Banking Problem Set 2 Answer Key

Econ 4721 Money and Banking Problem Set 2 Answer Key Econ 472 Money nd Bnking Problem Set 2 Answer Key Problem (35 points) Consider n overlpping genertions model in which consumers live for two periods. The number of people born in ech genertion grows in

More information

EE247 Lecture 4. For simplicity, will start with all pole ladder type filters. Convert to integrator based form- example shown

EE247 Lecture 4. For simplicity, will start with all pole ladder type filters. Convert to integrator based form- example shown EE247 Lecture 4 Ldder type filters For simplicity, will strt with ll pole ldder type filters Convert to integrtor bsed form exmple shown Then will ttend to high order ldder type filters incorporting zeros

More information

FAULT TREES AND RELIABILITY BLOCK DIAGRAMS. Harry G. Kwatny. Department of Mechanical Engineering & Mechanics Drexel University

FAULT TREES AND RELIABILITY BLOCK DIAGRAMS. Harry G. Kwatny. Department of Mechanical Engineering & Mechanics Drexel University SYSTEM FAULT AND Hrry G. Kwtny Deprtment of Mechnicl Engineering & Mechnics Drexel University OUTLINE SYSTEM RBD Definition RBDs nd Fult Trees System Structure Structure Functions Pths nd Cutsets Reliility

More information

Chapter 5: Coaxial Components and Rectangular Waveguide Components

Chapter 5: Coaxial Components and Rectangular Waveguide Components Chpter 5: Coil Components nd Rectngulr Wveguide Components The informtion in this wor hs een otined from sources elieved to e relile. The uthor does not gurntee the ccurc or completeness of n informtion

More information

Learning Outcomes. Computer Systems - Architecture Lecture 4 - Boolean Logic. What is Logic? Boolean Logic 10/28/2010

Learning Outcomes. Computer Systems - Architecture Lecture 4 - Boolean Logic. What is Logic? Boolean Logic 10/28/2010 /28/2 Lerning Outcomes At the end of this lecture you should: Computer Systems - Architecture Lecture 4 - Boolen Logic Eddie Edwrds eedwrds@doc.ic.c.uk http://www.doc.ic.c.uk/~eedwrds/compsys (Hevily sed

More information

Math 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1.

Math 314, Homework Assignment 1. 1. Prove that two nonvertical lines are perpendicular if and only if the product of their slopes is 1. Mth 4, Homework Assignment. Prove tht two nonverticl lines re perpendiculr if nd only if the product of their slopes is. Proof. Let l nd l e nonverticl lines in R of slopes m nd m, respectively. Suppose

More information

Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE. Date: Friday 16 th May 2008. Time: 14:00 16:00

Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE. Date: Friday 16 th May 2008. Time: 14:00 16:00 COMP20212 Two hours UNIVERSITY OF MANCHESTER SCHOOL OF COMPUTER SCIENCE Digitl Design Techniques Dte: Fridy 16 th My 2008 Time: 14:00 16:00 Plese nswer ny THREE Questions from the FOUR questions provided

More information

. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2

. At first sight a! b seems an unwieldy formula but use of the following mnemonic will possibly help. a 1 a 2 a 3 a 1 a 2 7 CHAPTER THREE. Cross Product Given two vectors = (,, nd = (,, in R, the cross product of nd written! is defined to e: " = (!,!,! Note! clled cross is VECTOR (unlike which is sclr. Exmple (,, " (4,5,6

More information

Lecture 3 Gaussian Probability Distribution

Lecture 3 Gaussian Probability Distribution Lecture 3 Gussin Probbility Distribution Introduction l Gussin probbility distribution is perhps the most used distribution in ll of science. u lso clled bell shped curve or norml distribution l Unlike

More information

Physics 43 Homework Set 9 Chapter 40 Key

Physics 43 Homework Set 9 Chapter 40 Key Physics 43 Homework Set 9 Chpter 4 Key. The wve function for n electron tht is confined to x nm is. Find the normliztion constnt. b. Wht is the probbility of finding the electron in. nm-wide region t x

More information

RTL Power Optimization with Gate-level Accuracy

RTL Power Optimization with Gate-level Accuracy RTL Power Optimiztion with Gte-level Accurcy Qi Wng Cdence Design Systems, Inc Sumit Roy Clypto Design Systems, Inc 555 River Oks Prkwy, Sn Jose 95125 2903 Bunker Hill Lne, Suite 208, SntClr 95054 qwng@cdence.com

More information

Vectors. The magnitude of a vector is its length, which can be determined by Pythagoras Theorem. The magnitude of a is written as a.

Vectors. The magnitude of a vector is its length, which can be determined by Pythagoras Theorem. The magnitude of a is written as a. Vectors mesurement which onl descries the mgnitude (i.e. size) of the oject is clled sclr quntit, e.g. Glsgow is 11 miles from irdrie. vector is quntit with mgnitude nd direction, e.g. Glsgow is 11 miles

More information

Experiment 6: Friction

Experiment 6: Friction Experiment 6: Friction In previous lbs we studied Newton s lws in n idel setting, tht is, one where friction nd ir resistnce were ignored. However, from our everydy experience with motion, we know tht

More information

Cypress Creek High School IB Physics SL/AP Physics B 2012 2013 MP2 Test 1 Newton s Laws. Name: SOLUTIONS Date: Period:

Cypress Creek High School IB Physics SL/AP Physics B 2012 2013 MP2 Test 1 Newton s Laws. Name: SOLUTIONS Date: Period: Nme: SOLUTIONS Dte: Period: Directions: Solve ny 5 problems. You my ttempt dditionl problems for extr credit. 1. Two blocks re sliding to the right cross horizontl surfce, s the drwing shows. In Cse A

More information

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding

Example A rectangular box without lid is to be made from a square cardboard of sides 18 cm by cutting equal squares from each corner and then folding 1 Exmple A rectngulr box without lid is to be mde from squre crdbord of sides 18 cm by cutting equl squres from ech corner nd then folding up the sides. 1 Exmple A rectngulr box without lid is to be mde

More information

Week 11 - Inductance

Week 11 - Inductance Week - Inductnce November 6, 202 Exercise.: Discussion Questions ) A trnsformer consists bsiclly of two coils in close proximity but not in electricl contct. A current in one coil mgneticlly induces n

More information

Words Symbols Diagram. abcde. a + b + c + d + e

Words Symbols Diagram. abcde. a + b + c + d + e Logi Gtes nd Properties We will e using logil opertions to uild mhines tht n do rithmeti lultions. It s useful to think of these opertions s si omponents tht n e hooked together into omplex networks. To

More information

Distributions. (corresponding to the cumulative distribution function for the discrete case).

Distributions. (corresponding to the cumulative distribution function for the discrete case). Distributions Recll tht n integrble function f : R [,] such tht R f()d = is clled probbility density function (pdf). The distribution function for the pdf is given by F() = (corresponding to the cumultive

More information

Rate and Activation Energy of the Iodination of Acetone

Rate and Activation Energy of the Iodination of Acetone nd Activtion Energ of the Iodintion of Acetone rl N. eer Dte of Eperiment: //00 Florence F. Ls (prtner) Abstrct: The rte, rte lw nd ctivtion energ of the iodintion of cetone re detered b observing the

More information

6.2 Volumes of Revolution: The Disk Method

6.2 Volumes of Revolution: The Disk Method mth ppliction: volumes of revolution, prt ii Volumes of Revolution: The Disk Method One of the simplest pplictions of integrtion (Theorem ) nd the ccumultion process is to determine so-clled volumes of

More information

COMPARISON OF SOME METHODS TO FIT A MULTIPLICATIVE TARIFF STRUCTURE TO OBSERVED RISK DATA BY B. AJNE. Skandza, Stockholm ABSTRACT

COMPARISON OF SOME METHODS TO FIT A MULTIPLICATIVE TARIFF STRUCTURE TO OBSERVED RISK DATA BY B. AJNE. Skandza, Stockholm ABSTRACT COMPARISON OF SOME METHODS TO FIT A MULTIPLICATIVE TARIFF STRUCTURE TO OBSERVED RISK DATA BY B. AJNE Skndz, Stockholm ABSTRACT Three methods for fitting multiplictive models to observed, cross-clssified

More information

Binary Representation of Numbers Autar Kaw

Binary Representation of Numbers Autar Kaw Binry Representtion of Numbers Autr Kw After reding this chpter, you should be ble to: 1. convert bse- rel number to its binry representtion,. convert binry number to n equivlent bse- number. In everydy

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

** Dpt. Chemical Engineering, Kasetsart University, Bangkok 10900, Thailand

** Dpt. Chemical Engineering, Kasetsart University, Bangkok 10900, Thailand Modelling nd Simultion of hemicl Processes in Multi Pulse TP Experiment P. Phnwdee* S.O. Shekhtmn +. Jrungmnorom** J.T. Gleves ++ * Dpt. hemicl Engineering, Ksetsrt University, Bngkok 10900, Thilnd + Dpt.hemicl

More information

2005-06 Second Term MAT2060B 1. Supplementary Notes 3 Interchange of Differentiation and Integration

2005-06 Second Term MAT2060B 1. Supplementary Notes 3 Interchange of Differentiation and Integration Source: http://www.mth.cuhk.edu.hk/~mt26/mt26b/notes/notes3.pdf 25-6 Second Term MAT26B 1 Supplementry Notes 3 Interchnge of Differentition nd Integrtion The theme of this course is bout vrious limiting

More information

0.1 Basic Set Theory and Interval Notation

0.1 Basic Set Theory and Interval Notation 0.1 Bsic Set Theory nd Intervl Nottion 3 0.1 Bsic Set Theory nd Intervl Nottion 0.1.1 Some Bsic Set Theory Notions Like ll good Mth ooks, we egin with definition. Definition 0.1. A set is well-defined

More information

Scalar and Vector Quantities. A scalar is a quantity having only magnitude (and possibly phase). LECTURE 2a: VECTOR ANALYSIS Vector Algebra

Scalar and Vector Quantities. A scalar is a quantity having only magnitude (and possibly phase). LECTURE 2a: VECTOR ANALYSIS Vector Algebra Sclr nd Vector Quntities : VECTO NLYSIS Vector lgebr sclr is quntit hving onl mgnitude (nd possibl phse). Emples: voltge, current, chrge, energ, temperture vector is quntit hving direction in ddition to

More information

How To Network A Smll Business

How To Network A Smll Business Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd processes. Introducing technology

More information

Treatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3.

Treatment Spring Late Summer Fall 0.10 5.56 3.85 0.61 6.97 3.01 1.91 3.01 2.13 2.99 5.33 2.50 1.06 3.53 6.10 Mean = 1.33 Mean = 4.88 Mean = 3. The nlysis of vrince (ANOVA) Although the t-test is one of the most commonly used sttisticl hypothesis tests, it hs limittions. The mjor limittion is tht the t-test cn be used to compre the mens of only

More information

Small Businesses Decisions to Offer Health Insurance to Employees

Small Businesses Decisions to Offer Health Insurance to Employees Smll Businesses Decisions to Offer Helth Insurnce to Employees Ctherine McLughlin nd Adm Swinurn, June 2014 Employer-sponsored helth insurnce (ESI) is the dominnt source of coverge for nonelderly dults

More information

DlNBVRGH + Sickness Absence Monitoring Report. Executive of the Council. Purpose of report

DlNBVRGH + Sickness Absence Monitoring Report. Executive of the Council. Purpose of report DlNBVRGH + + THE CITY OF EDINBURGH COUNCIL Sickness Absence Monitoring Report Executive of the Council 8fh My 4 I.I...3 Purpose of report This report quntifies the mount of working time lost s result of

More information

CHAPTER 11 Numerical Differentiation and Integration

CHAPTER 11 Numerical Differentiation and Integration CHAPTER 11 Numericl Differentition nd Integrtion Differentition nd integrtion re bsic mthemticl opertions with wide rnge of pplictions in mny res of science. It is therefore importnt to hve good methods

More information

and thus, they are similar. If k = 3 then the Jordan form of both matrices is

and thus, they are similar. If k = 3 then the Jordan form of both matrices is Homework ssignment 11 Section 7. pp. 249-25 Exercise 1. Let N 1 nd N 2 be nilpotent mtrices over the field F. Prove tht N 1 nd N 2 re similr if nd only if they hve the sme miniml polynomil. Solution: If

More information

5.6 POSITIVE INTEGRAL EXPONENTS

5.6 POSITIVE INTEGRAL EXPONENTS 54 (5 ) Chpter 5 Polynoils nd Eponents 5.6 POSITIVE INTEGRAL EXPONENTS In this section The product rule for positive integrl eponents ws presented in Section 5., nd the quotient rule ws presented in Section

More information

1. In the Bohr model, compare the magnitudes of the electron s kinetic and potential energies in orbit. What does this imply?

1. In the Bohr model, compare the magnitudes of the electron s kinetic and potential energies in orbit. What does this imply? Assignment 3: Bohr s model nd lser fundmentls 1. In the Bohr model, compre the mgnitudes of the electron s kinetic nd potentil energies in orit. Wht does this imply? When n electron moves in n orit, the

More information

Rotating DC Motors Part I

Rotating DC Motors Part I Rotting DC Motors Prt I he previous lesson introduced the simple liner motor. Liner motors hve some prcticl pplictions, ut rotting DC motors re much more prolific. he principles which eplin the opertion

More information

Review guide for the final exam in Math 233

Review guide for the final exam in Math 233 Review guide for the finl exm in Mth 33 1 Bsic mteril. This review includes the reminder of the mteril for mth 33. The finl exm will be cumultive exm with mny of the problems coming from the mteril covered

More information

How To Set Up A Network For Your Business

How To Set Up A Network For Your Business Why Network is n Essentil Productivity Tool for Any Smll Business TechAdvisory.org SME Reports sponsored by Effective technology is essentil for smll businesses looking to increse their productivity. Computer

More information

Version 001 Summer Review #03 tubman (IBII20142015) 1

Version 001 Summer Review #03 tubman (IBII20142015) 1 Version 001 Summer Reiew #03 tubmn (IBII20142015) 1 This print-out should he 35 questions. Multiple-choice questions my continue on the next column or pge find ll choices before nswering. Concept 20 P03

More information

NQF Level: 2 US No: 7480

NQF Level: 2 US No: 7480 NQF Level: 2 US No: 7480 Assessment Guide Primry Agriculture Rtionl nd irrtionl numers nd numer systems Assessor:.......................................... Workplce / Compny:.................................

More information

Small Business Networking

Small Business Networking Why network is n essentil productivity tool for ny smll business Effective technology is essentil for smll businesses looking to increse the productivity of their people nd business. Introducing technology

More information

Lesson 2.1 Inductive Reasoning

Lesson 2.1 Inductive Reasoning Lesson.1 Inutive Resoning Nme Perio Dte For Eerises 1 7, use inutive resoning to fin the net two terms in eh sequene. 1. 4, 8, 1, 16,,. 400, 00, 100, 0,,,. 1 8, 7, 1, 4,, 4.,,, 1, 1, 0,,. 60, 180, 10,

More information

Rotating DC Motors Part II

Rotating DC Motors Part II Rotting Motors rt II II.1 Motor Equivlent Circuit The next step in our consiertion of motors is to evelop n equivlent circuit which cn be use to better unerstn motor opertion. The rmtures in rel motors

More information

Section 1: Crystal Structure

Section 1: Crystal Structure Phsics 927 Section 1: Crstl Structure A solid is sid to be crstl if toms re rrnged in such w tht their positions re ectl periodic. This concept is illustrted in Fig.1 using two-dimensionl (2D) structure.

More information

Scalable Mining of Large Disk-based Graph Databases

Scalable Mining of Large Disk-based Graph Databases Sclle Mining of Lrge Disk-sed Grph Dtses Chen Wng Wei Wng Jin Pei Yongti Zhu Bile Shi Fudn University, Chin, {chenwng, weiwng1, 2465, shi}@fudn.edu.cn Stte University of New York t Bufflo, USA & Simon

More information

All pay auctions with certain and uncertain prizes a comment

All pay auctions with certain and uncertain prizes a comment CENTER FOR RESEARC IN ECONOMICS AND MANAGEMENT CREAM Publiction No. 1-2015 All py uctions with certin nd uncertin prizes comment Christin Riis All py uctions with certin nd uncertin prizes comment Christin

More information

Firm Objectives. The Theory of the Firm II. Cost Minimization Mathematical Approach. First order conditions. Cost Minimization Graphical Approach

Firm Objectives. The Theory of the Firm II. Cost Minimization Mathematical Approach. First order conditions. Cost Minimization Graphical Approach Pro. Jy Bhttchry Spring 200 The Theory o the Firm II st lecture we covered: production unctions Tody: Cost minimiztion Firm s supply under cost minimiztion Short vs. long run cost curves Firm Ojectives

More information