B.Sc. COMPUTER SCIENCE, BCA Allied Mathematics ALLIED COURSE I (AC) - ALGEBRA AND CALCULUS

Size: px
Start display at page:

Download "B.Sc. COMPUTER SCIENCE, BCA Allied Mathematics ALLIED COURSE I (AC) - ALGEBRA AND CALCULUS"

Transcription

1 UNIT I B.Sc. COMPUTER SCIENCE, BCA Allied Mthemtics ALLIED COURSE I (AC) - ALGEBRA AND CALCULUS Theory of Equtios: Reltio betwee roots & coefficiets Trsformtios of Equtios Dimiishig, Icresig & multiplyig the roots by costt- Formig equtios with the give roots Rolle s Theorem, Descrte s rule of Sigs(sttemet oly) simple problems. UNIT II Mtrices : Sigulr mtrices Iverse of o-sigulr mtri usig djoit method - Rk of Mtri Cosistecy - Chrcteristic equtio, Eige vlues, Eige vectors Cyley Hmilto s Theorem (proof ot eeded) Simple pplictios oly UNIT III Differetitio: Mim & Miim Cocvity, Coveity Poits of ifleio - Prtil differetitio Euler s Theorem - Totl differetil coefficiets (proof ot eeded ) Simple problems oly. UNIT IV Itegrtio : Evlutio of itegrls of types,, d, b si d b cos Evlutio usig Itegrtio by prts Properties of defiite itegrls Fourier Series i the rge (, π ) Odd & Eve Fuctios Fourier Hlf rge Sie & Cosie Series UNIT V Differetil Equtios: Vribles Seprbles Lier equtios Secod order of types ( D + b D + c ) y F ( ) where,b,c re costts d F ( ) is oe of the followig types (i) e K (ii) si (k) or cos (k) (iii), beig iteger (iv) e K F ().

2 Let us cosider ALGEBRA AND CALCULUS Uit I Theory of Equtios This polyomil i of degree provided. The equtio is obtied by puttig f() is clled lgebric equtio of degree. RELATIONS BETWEEN THE ROOTS AND COEFFICIENTS OF EQUATIONS Let the give equtio be Let,,, be its roots. sum of the roots tke oe t time sum of the product of the roots tke two t time sum of the product of the roots tke three t time filly we get. Problem: If α d β re the roots of, fid α + β, αβ. Solutio: Here α + β αβ. Problem: Solve the equtio, oe root beig + i. Solutio: Give equtio is cubic. Hece we hve roots. Oe root is (+i) α (sy) comple roots occur i pirs. β i is other root. To fid third root (sy)

3 Sum of the roots tke oe t time α + β +. i.e., + i + i + The roots of the give equtio re + i, i, -. Problem: Solve the equtio hvig give tht + is root. Solutio: Give equtio is cubic. Hece we hve three roots. Oe root is + i α Sice comple roots occur i pirs, i β is other root. Sum of the roots is α + β + i.e., + i + i Hece the roots of the give equtio re + i, i,. Problem: Solve the equtio which hs root +. Solutio: Give () This equtio is biqudrtic, i.e., fourth degree equtio. It hs roots. Give + is root which is clerly irrtiol. Sice irrtiol roots occur i pirs, is lso root of the give equtio.

4 [ ( + )] [ ( )] is fctor of () ALGEBRA AND CALCULUS i.e., is fctor. Dividig () by, we get (-) (-) Hece the quotiet is. Solvig this qudrtic equtio, we get. Hece the roots of the give equtio re +,,,. Problem: Form the equtio, with rtiol coefficiets oe root of whose roots is. Solutio: Oe root is i.e., i.e., Squrig o both sides we get Agi squrig, we get

5 , which is the required equtio. Problem: Form the equtio with rtiol coefficiets hvig + d + s two of its roots. Solutio: Give + d + i.e., [ ( + )] [ ( + )] re the fctors of the required equtio. Sice comple d irrtiol roots occur i pirs, we hve, re lso the roots of the required equtio. i.e., ( ) d ( ) re lso fctors of the required equtio. Hece the required equtio is, [ ( + )] [ ( + )] [ ( )] [ ( )] i.e., ( ( Simplifyig we get Problem: which is the required equtio. Solve the equtio whose roots re i A.P. Solutio: Let the roots be α d, α, α + d. Sum of the roots tke oe t time is, α d + α + α + d α

6 α is root of the give equtio. By divisio we hve, The reduced equtio is Solvig this qudrtic equtio we get the remiig two roots,. Hece the roots of the give equtio re,,. Problem: Fid the vlue of k for which the roots of the equtio re i A.P. Solutio: Give () Let the roots be α d, α, α + d. Sum of the roots tke oe t time is, α d + α + α + d α i.e., α - i.e., α - is root of (). put - i (), we get k. Problem: Solve the equtio whose roots re i G.P. 6

7 Solutio: ALGEBRA AND CALCULUS Give () Let the roots be, α, αr Product of the roots tke three t time is. α. αr i.e., i.e., α. i.e., α is root of the give equtio () i.e., is root of the give equtio () i.e., ( - is fctor of (). (-) (-) Hece the quotiet is i.e., Solvig this qudrtic equtio we get Hece the roots of the give equtio re. 7

8 Problem: Fid the coditio tht the roots of the equtio Solutio: my be i G.P. Give () Let the roots be, α, αr Product of the roots tke three t time. α. αr r i.e., r () But α is root of the equtio (). Put α i (), we get, () Substitutig () i () we get i.e., i.e., r Hece the required coditio is p r q. Trsformtio of Equtios: Problem: If the roots of re -,, 9, fid the equtio whose roots re, -, -9.

9 Solutio: Give () The roots re -,, 9. Now we fid equtio whose roots re, -, -9 ie., to fid equtio whose roots re the roots of () but the sigs re chged. Hece i () we hve to chge the sig of odd powers of. Hece the required equtio is i.e., This gives the required equtio. Problem: Multiply the roots of the equtio by. Solutio: Give () To multiply the roots of () by, we hve to multiply the successive coefficiets begiig with the secod by i.e., i.e., which is the required equtio. Problem: Remove the frctiol coefficiets from the equtio. 9

10 Solutio: ALGEBRA AND CALCULUS Give () Multiply by the roots of () by m, we get m m m () If m (L.C.M. of d ), the frctios will be removed. Put m i (), we get i.e.,. Problem: Solve the equtio 6 give tht its roots re i H.P. Solutio: Give () Its roots re i H.P. to i (), we get 6 6 Now the roots of () re i A.P. (Sice H.P. is reciprocl of A.P.). Let the roots of () be d,, d. Sum of the roots d d Product of the roots tke t the time is ( d) ( d) d.

11 Cse(i) : ALGEBRA AND CALCULUS Whe d i. e.,,,. The roots of the give equtio re the reciprocl of the roots of i. e.,,,. d, re roots of the roots of re,, Cse (ii) : Whe d i. e.,,,. The roots of the give equtio re the reciprocl of the roots of i. e.,,, d., re roots of the roots of re,, Problem: Dimiish the roots of 7 by d fid the trsformed equtio. Solutio : Dimiishig the roots by, we get (costt term of the - - trsformed equtio) (coefficiet of ) (coefficiet of ) (coefficiet of ) (coefficiet of i the trsformed equtio) The trsformed equtio whose roots re less by of the give equtio is

12 Problem: Icrese by 7 the roots of the equtio 7 d fid the trsformed equtio. Solutio : Icresig by 7 the roots of the give equtio is the sme s dimiishig the roots by (costt term of the trsformed equtio) (coefficiet of ) (coefficiet of ) (coefficiet of ) (coefficiet of i the trsformed equtio) The trsformed equtio is Problem: Fid the equtio whose roots re the roots of icresed by. Solutio : (costt term of the - - trsformed equtio) (coefficiet of ) (coefficiet of ) (coefficiet of ) (coefficiet of i the trsformed equtio) The trsformed equtio is 9.

13 Problem: If,, re the roots of the equtio 6, fid equtio whose roots re,,. Solutio : The trsformed equtio is. i.e., the roots re,,. i.e.,,, i.e.,,,. Problem: Fid the trsformed equtio with sig chged Solutio: Give tht Give sig Now the trsformed equtio which is the required equtio.

14 Nture of the Roots: Problem: Determie completely the ture of the roots of the equtio. Solutio: Give tht There re times sig chged. There eist positive roots. Put - There is time sig chged. There is oly oe positive root. There re rel roots. The degree of the equtio is. Number of imgiry roots degree of equtio umber of rel roots The umber of imgiry roots.

15 UNIT - MATRICES A mtri is defied to be rectgulr rry of umbers rrged ito rows d colums. It is writte s follows:- m m ` m m Specil Types of Mtrices: (i) A row mtri is mtri with oly oe row. E.g., [ ]. (ii) A colum mtri is mtri with oly oe colum. E.g.,. (iii) Squre mtri is oe i which the umber of rows is equl to the umber of colums. If A is the squre mtri. m m ` m m the the determit is clled the determit of the mtri A d it is deoted by A or deta. (iv) Sclr mtri is digol mtri i which ll the elemets log the mi digol re equl.

16 6 E.g., (v) Uit mtri is sclr mtri i which ll the elemets log the mi digol re uity. I, I (vi) Null or Zero mtri. If ll the elemets i mtri re zeros, it is clled ull or zero mtri d is deoted by. (vii) Trspose mtri. If the rows d colums re iterchged i mtri A, we obti secod mtri tht is clled the trspose of the origil mtri d is deoted by A t. (viii) Additio of mtrices. Mtrices re dded, by ddig together correspodig elemets of the mtrices. Hece oly mtrices of the sme order my be dded together. The result of dditio of two mtrices is mtri of the sme order whose elemets re the sum of the sme elemets of the correspodig positios i the origil mtrices. E.g., b b b b b b b b b b b b Problem: Give ; 6 B A ; compute A-B

17 Solutio : ALGEBRA AND CALCULUS A B Problem: Fid vlues of, y, z d tht stisfy the mtri reltioship y z Solutio : From the equlity of these two mtices we y z Solvig these equtios we get, y, z, 7 Multiplictio of Mtrices. get the equtios If A is m mtri with rows A, A,, A m d B is p mtri with colums B, B,.., B p, the the prodduct AB is m p mtri C whose elemets re give by the formul C ij A i. B j. Hece C AB 7

18 Iverse of Mtri Problem: Fid the iverse of the mtri Solutio: ALGEBRA AND CALCULUS det ( ) ( + ) (-6) (-) Form the mtri of mior determits:. 6 6 Adjust the sigs of every other elemet (strtig with the secod etry): 6 6 Tke the trspose d divide by the determit: 6 So the iverse mtri is Problem: Show tht A stisfies the equtio A A I. Hece determie its iverse. Solutio: A 9 9 9

19 9 A I A A I Therefore A A I. Multiplyig by A -, we hve A - A A - A A - I i.e., A I A - Therefore A - A I Therefore A -. Rk of Mtri A sub-mtri of give mtri A is defied to be either A itself or rry remiig fter certi rows d colums re deleted from A. The determits of the squre sub-mtrices re clled the miors of A. The rk of m mtri A is r iff every mior i A of order r + vishes while there is t lest oe mior of order r which does ot vish.

20 Problem: Fid the rk of the mtri 6. Solutio: Mior of third order 6. The miors of order re obtied by deletig y oe row d y oe colum. Oe of the miors of orders is 6 Its vlue is. Hece the rk of the give mtri is. Rk of Mtri by Elemetry Trsformtios: Problem: Fid the rk of the mtri A 7. Solutio: The give mtri is A 6 ~ 6 R R R R R R ~ ) ( 6 R R ~ 6 R R R ~ C C C C C C

21 ~ ~ Hece A R C ALGEBRA AND CALCULUS C 6 R Hece the rk of the give mtri is. C which is uit mtri of order. Procedure for fidig the solutios of system of equtios: Let the give system of lier equtios be b b m + m + + m b m Step : Costruct the coefficiet mtri which is deoted by A m m ` m m Step : Costruct the ugmeted mtri which is deoted by [A, B] [ A, B] m m m Step : Fid the rks of both the coefficiet mtri d ugmeted mtri which re deoted by R(A) d R(A, B). Step : Compre the rks of R (A) d R(A, B) we hve the followig results. () If R(A) R(A, B) (umber of ukows) the the give system of equtios re cosistet d hve uique solutios. b b b b m

22 (b) If R(A) R(A, B) < (umber of ukows) the the give system of equtios re cosistet d hve ifiite umber of solutios. (c) If R(A) R(A, B) the the give system of equtios re icosistet (tht is the give system of equtios hve o solutio). Problem: Test for cosistecy d hece solve.,, z y z z y Solutio: The coefficiet mtri A The ugmeted mtri [A, B] ~ ~ 9 R R R R R R ~ 9 R R ~ 9 R R ~ R R Here rk of coefficiet mtri is. Rk of ugmeted mtri is. Hece the give system of equtios re cosistet d hve uique solutio.

23 Problem: Test the cosistecy of the followig system of equtios d if cosistet solve y z, y z, 7y z. Solutio: The coefficiet mtri A The ugmeted mtri [A, B] ~ 7 7 ~ R ~ R ~ ~ R R R Here rk of coefficiet mtri is R(A). Rk of ugmeted mtri is R(A, B). i.e., R(A) R(A, B) < (the umber of ukows) Hece the give system of equtios re cosistet but hve ifiite umber of solutios. Here the reduced system is y +z + y + z z i.e., y z z ( ) 6 z 6 k z i.e.,, y, z k where z k is the prmeter. R R R R R R

24 Solutio of Simulteous Equtios Problem: Solve the system of equtios Solutio: It c be represeted s: To see whether solutio eists we eed to fid This determit is ALGEBRA AND CALCULUS y z 6 y z 6. y z 6 y 6. z det (-) (-7) + (-) - Therefore we kow tht the equtios do hve uique solutio. To fid the solutio we eed to fid the iverse of the mtri.. Fid the determit: we hve lredy foud tht this is -. Form the mtri of mior determits (which, for prticulr etry i the mtri, is the determit of the by mtri tht is left whe the row d colum cotiig the etry re deleted): 7 Adjust the sigs of every other elemet (strtig with the secod etry): 7 Tke the trspose d divide by the determit: So the iverse mtri is Hece the solutios to the equtios re foud by Therefore., y - d z. y z

25 Cyley Hmilto theorem: Every squre mtri stisfies its ow chrcteristic equtio. Problem: Verify Cyley Hmilto theorem for the mtri iverse of A. Solutio : The chrcteristic equtio of mtri A is λ λ (++6) + λ(--+) [(-)-(-)+(-)] λ -λ - λ+, which is the chrcteristic equtio. By Cyley Hmilto theorem, we hve to prove A -A - A+ 6 d hece fid the A A.A A A A A -A - A+I Hece the theorem is verified. To fid A - We hve A -A - A+I I - A +A + A A - -A -A+ I A -

26 Problem: Fid ll the eige vlues d eige vectors of the mtri A Solutio : Give A The chrcteristic equtio of the mtri is λ λ (++) + λ(-++) [(-)-(-)-(-)] λ - λ - λ+, which is the chrcteristic equtio λ is root. The other roots re λ - λ - (λ -)( λ +) λ, - Hece λ,, -. The eige vectors of the mtri A is give by (A- λi)x i.e. (- λ) (- λ)..() (- λ) Whe λ, equtio () becomes Tke first d secod equtio,

27 Whe λ -, equtio () becomes Whe λ, equtio () becomes Hece Eige vector 7

28 Problem: Fid ll the eige vlues d eige vectors of Solutio : Give A The chrcteristic equtio of the mtri is λ λ (++) + λ(++) [()-()+(-)] λ -7 λ + λ-, which is the chrcteristic equtio λ is root. -6 The other roots re λ -6λ+ (λ -)( λ -) λ, Hece λ,,. The eige vectors of the mtri A is give by (A- λi)x i.e. (- λ) + + +(- λ) +..() + +(- λ) Whe λ, equtio () becomes Here ll the equtios re sme. Put, we get +

29 - For λ, put,we get + - Whe λ, equtio() becomes (tkig first d secod equtio) 6. Hece Eige vector 9

30 Problem: Fid the eige vlues d eige vectors of Solutio : The chrcteristic equtio of mtri A is )] ( () ) [( ) ( ) ( λ is root. The other roots re, ) )( ( Hece λ,, - The eige vectors of mtri A is give by ) ( ) ( ) ( ) ( X I A () Whe λ,equtio () becomes X

31 Whe λ -,Equtio () becomes ALGEBRA AND CALCULUS - X Whe λ, Equtio () becomes (tkig first d secod equtio) X Hece Eige vector

32 Uit III Mim Ad Miim If cotiuous fuctio icreses up to certi vlue d the decreses, tht vlue is clled mimum vlue of the fuctio. If cotiuous fuctio decreses up to certi vlue d the icreses, tht vlue is clled miimum vlue of the fuctio. Theorem: If, the f() hs mimum if d miimum if. Problem: Fid the mim d miim of the fuctio 6. Solutio: Let f() be 6. At the mimum or miimum poit f () Here f () (-) (+) d - give mimum or miimum. To distiguish betwee the mimum d miimum,we eed Whe, Whe -, - gives the mimum d gives the miimum. Hece Mimum vlue f(-) d Miimum vlue f() -7. Problem: Fid the mimum vlue of for positive vlues of. Solutio : Let f() be

33 At mimum or miimum,. log. e., i.e., - ve. e gives mimum. Mimum vlue of the fuctio f(e). Cocvity d Coveity, Poits of ifleio: If the eighbourhood of poit P o curve is bove the tget t P, it is sid to be Cocve upwrds; if the curve is below the tget t P, it is sid to be cocve dowwrds or cove upwrds. If t poit P, curve chges its cocvity from upwrds to dowwrds or vice vers, P is clled poit of ifleio. Problem: For wht vlues of is the curve upwrds? cocve upwrds d whe is it cove Solutio: The, If, is egtive d so cove upwrds. If, is positive d so cocve upwrds. If, d so there is poit of ifleio t. i.e., t the poit

34 Prtil Differetitio ALGEBRA AND CALCULUS Let u f(, y) be fuctio of two idepedet vribles. Differetitig u w.r.t. keepig y costt is kow s the prtil differetil coefficiet of u w.r.t.. It is deoted by. mes differetite u w.r.t. keepig y costt. Similrly if we differetite u w.r.t. y keepig costt is kow s the prtil differetil coefficiet of u w.r.t. y. It is deoted by. mes differetite u w.r.t. y keepig costt. Symboliclly, if u f(, y), the. Problem: If u log ( + y + z ), prove tht. Solutio: Give u log ( + y + z ) () Similrly ()

35 () Addig (), () d () we get. Problem: If u log(t + ty + tz), show tht. Solutio: Give u log(t + ty + tz) si () Similrly, siy () siz () Addig (), () d () we get

36 Euler s Theorem o Homogeeous Fuctio ALGEBRA AND CALCULUS Theorem: If u is homogeeous fuctio of degree i d y, the. Problem: If u, show tht. Solutio: Give u i.e., si u si u f, where f si u is homogeeous fuctio of degree. By Euler s theorem. Problem: Verify Euler s Theorem whe u + y + z + yz. Solutio: + yz. y + z. z + y. ( + yz) + y (y + z) + z (z + y) ( + y + z + yz) u. 6

37 Totl Differetil Coefficiet: ALGEBRA AND CALCULUS Problem: Fid where u, e t, y e t sit d z e t cost. Solutio: + + e t + y (e t sit + e t cost) + z (e t cost - e t sit) e t ( + y sit + y cost + z cost z sit) e t (e t + e t si t + e t sit cost + e t cos t - e t sit cost) e t. e t e t. Problem: If + y + y, fid. Solutio: + y + y, i.e., f(, y). y y. 7

38 UNIT IV Evlutio of Itegrls & Fourier Series Itegrls of the form Problem: Evlute. Solutio: Put + y; d dy. Problem: Evlute. Solutio: Put y; d dy

39 Itegrl of the form Problem: Evlute Solutio: Let + A ( ) + B + A ( ) + B Equtig coefficiet of o both sides we get A A Equtig costt coefficiets we get, - A + B B A ( ) +. log ( + log ( + log ( + log ( +. 9

40 Itegrls of the form Problem: Evlute Solutio: Itegrl of the form Problem: Evlute. Solutio: Let + A ( ) + B + A ( +) + B Equtig coefficiet of o both sides we get -A A - Equtig costt coefficiets we get, A + B B - A +. + ( + )

41 + ALGEBRA AND CALCULUS +. Properties of Defiite Itegrls: where If f() is odd fuctio i.e., f(-) - f() the 7. If f() is eve fuctio i.e., f(-) f() the Problem: Evlute Solutio: Let I () Also I Addig () d () we get I ()

42 I I. Problem: Evlute. Solutio: Let I () Also I () Addig () d () we get I I () To evlute Put y, d dy. Whe, y ;, y

43 I i.e., () Substitutig () i (), we get I I + I i.e.,. FOURIER SERIES Prticulr Cses Cse (i) If f() is defied over the itervl (,l). f() [ cos b si ] l l b l l l l l l f ( ) d f ( )cos f ( )si If f() is defied over the itervl (, ). l l d, d, f() [ cos b si ] f ( ) d,,

44 f ( )cosd,,,.. b f ( )si d,,.. Cse (ii) If f() is defied over the itervl (-l, l). f() [ cos b si ] l l l l l l l l f ( ) d f ( )cos l d,, l b f ( )si d, l l l,, If f() is defied over the itervl (-, ). f() [ cos b si ] f ( ) d f ( ) cosd,,,.. b f ( ) si d,,..

45 Problem: Obti the Fourier epsio of f() i - < < Solutio: f ( ) d ( ) d f ( )cosd ( ) cosd Here we use itegrtio by prts, so tht b ( si ( )si d ) cos cos ( ) Usig the vlues of, d b i the Fourier epsio we get, f ( ) f ( ) ( ) si cos b si ( ) si This is the required Fourier epsio of the give fuctio.

46 Problem: Obti the Fourier epsio of f()e - i the itervl (-, ). Deduce tht cosech Solutio: Here, e e e e ( d ) e sih cos d e cos si ( ) sih b e si d e si cos Thus, ( ) sih f() sih For,, the series reduces to or f() or sih sih sih sih sih sih ( ) ( ( ) ( cos sih si ) ( ) ) 6

47 Thus, cosech This is the desired deductio. ALGEBRA AND CALCULUS ( ) Problem: Obti the Fourier epsio of f() over the itervl (-, ). Deduce tht 6 Solutio: The fuctio f() is eve. Hece f ( ) d d or f ( ) d f ( ) cos d f ( )cosd, sice f()cos is eve cosd Itegrtig by prts, we get ( ) si cos si Also, b f ( )si d sice f()si is odd. 7

48 Thus ALGEBRA AND CALCULUS f ( ) 6 ( ) cos Hece,... 6 Problem: Obti the Fourier epsio of f ( ),, Deduce tht Solutio: Here, f ( ) d f ( ) d d f ( )cos d cosd f ( )cos d sice f()cos is eve. Also, b si ( ) cos f ( )si d, sice f()si is odd

49 Thus the Fourier series of f() is For, we get or Thus, f ( ) ALGEBRA AND CALCULUS ( ) cos f ( ) ( ) cos cos( ) ( ) ( ) or This is the series s required. Problem: Obti the Fourier epsio of, f(), Deduce tht Solutio: Here, d d ( ( Fourier series is b f() ) ) cos d si d cos d si d ( ) ( ) cos si 9

50 Note tht the poit is poit of discotiuity of f(). Here f( + ), f( - )- t. Hece [ f ( ) f ( )] The Fourier epsio of f() t becomes or [( [( Simplifyig we get, ) ] ) ] Problem: Obti the Fourier series of f() - over the itervl (-,). Solutio: The give fuctio is eve, s f(-) f(). Also period of f() is -(-) Here ( Itegrtig by prts, we get f ( ) d f ( ) d ) d f ( )cos( f ( )cos( ) d ) d ( ) cos( ) d ( ) The Fourier series of f() is f() si ( ) s f() cos( ) is eve cos ( ) b f ( )si( ) d, sice f()si( ) is odd. ( ) cos( ) ( ) si ( )

51 Problem: Obti the Fourier epsio of f(),, ALGEBRA AND CALCULUS Deduce tht Solutio: The period of f() is Also f(-) f(). Hece f() is eve Also, Thus puttig, we get b / / f() f() / / / / / / / f ( ) d d f ( )cos ( f ( )cos si ) f ( )si ( ) ( ) / / d d cos / d f ( ) d cos /

52 or Thus, HALF-RANGE FOURIER SERIES The Fourier epsio of the periodic fuctio f() of period l my coti both sie d cosie terms. My time it is required to obti the Fourier epsio of f() i the itervl (,l) which is regrded s hlf itervl. The defiitio c be eteded to the other hlf i such mer tht the fuctio becomes eve or odd. This will result i cosie series or sie series oly. Sie series : Suppose f() () is give i the itervl (,l). The we defie f() - (-) i (-l,). Hece f() becomes odd fuctio i (-l, l). The Fourier series the is where f ( ) b si () l b l l f ( )si l The series () is clled hlf-rge sie series over (,l). d Puttig l i (), we obti the hlf-rge sie series of f() over (, ) give by Cosie series : Let us defie f ( ) b si b f ( )si d f ( ) ( ) ( ) i (,l)... give i (-l,)..i order to mke the fuctio eve. The the Fourier series of f() is give by f ( ) cos () l where, l l l l f ( ) d f ( )cos l d

53 The series () is clled hlf-rge cosie series over (,l) Puttig l i (), we get f ( ) where Problem: Epd f() ( -) s hlf-rge sie series over the itervl (, ). Solutio: We hve, b Itegrtig by prts, we get b The sie series of f() is f ( ) ( f ( )si d ( )si d ) f ( ) d cos f ( )cos d cos,,, ( ) si.. si ( ) cos Problem: Obti the cosie series of Solutio:, f ( ) over (, ), Here d ( cos d ) d ( )cos d

54 Performig itegrtio by prts d simplifyig, we get ( ) cos,,6,,... Thus, the Fourier cosie series is cos cos6 cos f() Problem: Obti the hlf-rge cosie series of f() c- i <<c Solutio: Here c ( c ) d c c c ( c )cos c c Itegrtig by prts d simplifyig we get, d c ( ) The cosie series is give by c f() c ( ) cos c

55 UNIT-V DIFFERENTIAL EQUATIONS Defiitio: A differetil equtio is equtio i which differetil coefficiets occur. Differetil equtios re of two types(i) Ordiry d (ii) Prtil. A ordiry differetil equtio is oe which sigle idepedet vrible eters, either eplicity or implicity. For emple, dy d d d d si, dr y dy y d m y si re ordiry differetil equtios. Vrible seprble. Suppose equtio is of the form f ( ) d F( y) dy. We c directly itegrte this equtio d the solutio is f ( ) d F( y) dy c, where c is rbitrry costt. dy y Problem: Solve d Solutio: dy dy We hve. y Itegrtig, si - y + si - c. dy Problem: Solve ty cot. d Solutio: dy ty cot d ty dy cot d

56 t y dy cot d log secy log si + logc log secy log si logc log sec y si log c sec y c. si Problem: Solve t sec y dy + ty sec d Solutio: t sec y dy - ty sec d sec t y y sec t dy y y dy put t ty sec t sec t d d put u t dt sec y dy du sec (- d) log t - log u + log c log t + log u log c log (tu) log c tu c t y t c. Problem: Solve sec dy + secy d Solutio: dy sec y sec dy - secy d d sec cos y dy cos d si y - si + c si + si y c. 6

57 Lier Equtio: ALGEBRA AND CALCULUS A differetil equtio is sid to be lier whe the depedet vrible d its derivtives occur oly i the first degree d o products of these occur. The lier equtio of the first order is of the form fuctios of oly. dy d Py Q, where P d Q re Problem: Solve ( + dy ) + y. d Solutio: Divided by + (+ ) (+ ) dy d y dy d y This is of the form dy d Py Q. P d Q The solutio is y e Pd Q e Pd d c y e d e d d c () Pd e e d put t + dt d e d dt t e e logt t 7

58 e d +. () Usig () i (), y ( + ) ( ) d c y ( + ) d c y ( + ) c. Problem: Solve dy + y sec t. d Solutio: This is of the form dy d Py Q. The solutio is y e Pd Q e Pd d c P sec & Q t y e sec d t e sec d d c () Nowe sec d e log(sec t) sec t () y (sec + t) t (sec + t) d c t sec d + t d c sec ( sec ) d sec sec d sec t c. d

59 dy Problem: Solve - t y - si. d ALGEBRA AND CALCULUS Solutio: This is of the form dy d Py Q. The solutio is y e Pd Q e Pd d c P - t & Q - si y e t d si e t d d c () Nowe t d e logsec sec - y sec si ( sec ) d c si sec d c si d c cos t d c - y sec log sec + c. Problem: Solve dy cos + y t. d Solutio: Divided by cos. cos dy y t cos d cos cos dy ysec t sec d P sec & Q t sec The solutio is y e Pd Q e Pd d c 9

60 y e sec d t sec e sec d d c () Nowe sec d e t y e t t sec e t d c put t t dt sec d y e t t t e dt c t. e t - e t e t (t ) + c y e t e t ( t ) + c Problem: Solve ( + dy ) + y cos. d Solutio: Divided by + (+ ) (+ ) dy d y dy d y cos cos This is of the form dy d Py Q. P cos d Q The solutio is y e Pd Q e Pd d c y e d cos e d d c () Pd e e d put t + 6

61 dt d ALGEBRA AND CALCULUS e d dt t e e logt t e d +. () Usig () i (), y ( + ) cos ( ) d c y ( + ) y ( + ) cos d si c. c LINEAR DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS Problem: Solve (D + D + 6) y e. Solutio: To fid the C.F. solve (D + D + 6) y. The uiliry equtio is m + m + 6. Solvig, m - d -. C.F. A e - + B e -. P.I. e D D 6 e o replcig D by. y A e - + B e - + e. 6

62 Problem: Solve (D md + m ) y e m. Solutio: ALGEBRA AND CALCULUS To fid the C.F. solve (D md + m ) y. The uiliry equtio is k - mk + m. i.e., (k m), k m twice. C.F. e m (A + B). P.I. m e (k - m) m e y e m (A + B + ). Problem: Solve (D - D + ) y si. Solutio: To fid the C.F. solve (D + D + 6) y. The uiliry equtio is m - m +. Solvig, m d. C.F. A e + B e. P.I. si D D si 9 D, put D - -9 si 7 D 7 7 D D 7si D(si ) 9 9D 7si (cos ) 9 9( 9) 6

63 7si 9cos 9 7si 9cos ALGEBRA AND CALCULUS 7si 9cos y C.F. + P.I. A e + B e 7si 9cos. Problem: Solve Solutio: d y d dy y d. (D + D + ) y To fid the C.F. solve (D + D + ) y. The uiliry equtio is m + m +. m... i - i α-, β C.F. e - (A cos + B si ) P.I. D D 6

64 6 D D D D D D.... D D D D D D D D D 9 D D D (Neglectig Higher Powers) 9 ) ( ) ( ) ( D D D 9 () ) ( y C.F. + P.I. e - (A cos + B si ) + 9.

65 Problem: Solve (D + ) y e si. Solutio: The uiliry equtio m +. m - m m i. C.F. e (A cos + B si) A cos + B si P.I. e si D e si, replce D by D+ D D e si D e si, replce D by - D e si D D D e [D(si ) si ] 6D 6 e [D(si ) 6( ) si ] 6 e [cos si ] y C.F. + P.I. A cos + B si e [cos si ]. 6

Chapter 04.05 System of Equations

Chapter 04.05 System of Equations hpter 04.05 System of Equtios After redig th chpter, you should be ble to:. setup simulteous lier equtios i mtrix form d vice-vers,. uderstd the cocept of the iverse of mtrix, 3. kow the differece betwee

More information

Repeated multiplication is represented using exponential notation, for example:

Repeated multiplication is represented using exponential notation, for example: Appedix A: The Lws of Expoets Expoets re short-hd ottio used to represet my fctors multiplied together All of the rules for mipultig expoets my be deduced from the lws of multiplictio d divisio tht you

More information

MATHEMATICS FOR ENGINEERING BASIC ALGEBRA

MATHEMATICS FOR ENGINEERING BASIC ALGEBRA MATHEMATICS FOR ENGINEERING BASIC ALGEBRA TUTORIAL - INDICES, LOGARITHMS AND FUNCTION This is the oe of series of bsic tutorils i mthemtics imed t begiers or yoe wtig to refresh themselves o fudmetls.

More information

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is 0_0605.qxd /5/05 0:45 AM Page 470 470 Chapter 6 Additioal Topics i Trigoometry 6.5 Trigoometric Form of a Complex Number What you should lear Plot complex umbers i the complex plae ad fid absolute values

More information

SOME IMPORTANT MATHEMATICAL FORMULAE

SOME IMPORTANT MATHEMATICAL FORMULAE SOME IMPORTANT MATHEMATICAL FORMULAE Circle : Are = π r ; Circuferece = π r Squre : Are = ; Perieter = 4 Rectgle: Are = y ; Perieter = (+y) Trigle : Are = (bse)(height) ; Perieter = +b+c Are of equilterl

More information

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series 8 Fourier Series Our aim is to show that uder reasoable assumptios a give -periodic fuctio f ca be represeted as coverget series f(x) = a + (a cos x + b si x). (8.) By defiitio, the covergece of the series

More information

Application: Volume. 6.1 Overture. Cylinders

Application: Volume. 6.1 Overture. Cylinders Applictio: Volume 61 Overture I this chpter we preset other pplictio of the defiite itegrl, this time to fid volumes of certi solids As importt s this prticulr pplictio is, more importt is to recogize

More information

MATHEMATICS SYLLABUS SECONDARY 7th YEAR

MATHEMATICS SYLLABUS SECONDARY 7th YEAR Europe Schools Office of the Secretry-Geerl Pedgogicl developmet Uit Ref.: 2011-01-D-41-e-2 Orig.: DE MATHEMATICS SYLLABUS SECONDARY 7th YEAR Stdrd level 5 period/week course Approved y the Joit Techig

More information

1. MATHEMATICAL INDUCTION

1. MATHEMATICAL INDUCTION 1. MATHEMATICAL INDUCTION EXAMPLE 1: Prove that for ay iteger 1. Proof: 1 + 2 + 3 +... + ( + 1 2 (1.1 STEP 1: For 1 (1.1 is true, sice 1 1(1 + 1. 2 STEP 2: Suppose (1.1 is true for some k 1, that is 1

More information

Soving Recurrence Relations

Soving Recurrence Relations Sovig Recurrece Relatios Part 1. Homogeeous liear 2d degree relatios with costat coefficiets. Cosider the recurrece relatio ( ) T () + at ( 1) + bt ( 2) = 0 This is called a homogeeous liear 2d degree

More information

Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed.

Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed. This documet was writte ad copyrighted by Paul Dawkis. Use of this documet ad its olie versio is govered by the Terms ad Coditios of Use located at http://tutorial.math.lamar.edu/terms.asp. The olie versio

More information

Harold s Calculus Notes Cheat Sheet 26 April 2016

Harold s Calculus Notes Cheat Sheet 26 April 2016 Hrol s Clculus Notes Chet Sheet 26 April 206 AP Clculus Limits Defiitio of Limit Let f e fuctio efie o ope itervl cotiig c let L e rel umer. The sttemet: lim x f(x) = L mes tht for ech ε > 0 there exists

More information

CHAPTER-10 WAVEFUNCTIONS, OBSERVABLES and OPERATORS

CHAPTER-10 WAVEFUNCTIONS, OBSERVABLES and OPERATORS Lecture Notes PH 4/5 ECE 598 A. L Ros INTRODUCTION TO QUANTUM MECHANICS CHAPTER-0 WAVEFUNCTIONS, OBSERVABLES d OPERATORS 0. Represettios i the sptil d mometum spces 0..A Represettio of the wvefuctio i

More information

Infinite Sequences and Series

Infinite Sequences and Series CHAPTER 4 Ifiite Sequeces ad Series 4.1. Sequeces A sequece is a ifiite ordered list of umbers, for example the sequece of odd positive itegers: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29...

More information

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here).

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here). BEGINNING ALGEBRA Roots ad Radicals (revised summer, 00 Olso) Packet to Supplemet the Curret Textbook - Part Review of Square Roots & Irratioals (This portio ca be ay time before Part ad should mostly

More information

Section 11.3: The Integral Test

Section 11.3: The Integral Test Sectio.3: The Itegral Test Most of the series we have looked at have either diverged or have coverged ad we have bee able to fid what they coverge to. I geeral however, the problem is much more difficult

More information

A. Description: A simple queueing system is shown in Fig. 16-1. Customers arrive randomly at an average rate of

A. Description: A simple queueing system is shown in Fig. 16-1. Customers arrive randomly at an average rate of Queueig Theory INTRODUCTION Queueig theory dels with the study of queues (witig lies). Queues boud i rcticl situtios. The erliest use of queueig theory ws i the desig of telehoe system. Alictios of queueig

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

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx SAMPLE QUESTIONS FOR FINAL EXAM REAL ANALYSIS I FALL 006 3 4 Fid the followig usig the defiitio of the Riema itegral: a 0 x + dx 3 Cosider the partitio P x 0 3, x 3 +, x 3 +,......, x 3 3 + 3 of the iterval

More information

THE ARITHMETIC OF INTEGERS. - multiplication, exponentiation, division, addition, and subtraction

THE ARITHMETIC OF INTEGERS. - multiplication, exponentiation, division, addition, and subtraction THE ARITHMETIC OF INTEGERS - multiplicatio, expoetiatio, divisio, additio, ad subtractio What to do ad what ot to do. THE INTEGERS Recall that a iteger is oe of the whole umbers, which may be either positive,

More information

Summation Notation The sum of the first n terms of a sequence is represented by the summation notation i the index of summation

Summation Notation The sum of the first n terms of a sequence is represented by the summation notation i the index of summation Lesso 0.: Sequeces d Summtio Nottio Def. of Sequece A ifiite sequece is fuctio whose domi is the set of positive rel itegers (turl umers). The fuctio vlues or terms of the sequece re represeted y, 2, 3,...,....

More information

MATHEMATICAL ANALYSIS

MATHEMATICAL ANALYSIS Mri Predoi Trdfir Băl MATHEMATICAL ANALYSIS VOL II INTEGRAL CALCULUS Criov, 5 CONTENTS VOL II INTEGRAL CALCULUS Chpter V EXTENING THE EFINITE INTEGRAL V efiite itegrls with prmeters Problems V 5 V Improper

More information

Chapter 5: Inner Product Spaces

Chapter 5: Inner Product Spaces Chapter 5: Ier Product Spaces Chapter 5: Ier Product Spaces SECION A Itroductio to Ier Product Spaces By the ed of this sectio you will be able to uderstad what is meat by a ier product space give examples

More information

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5

0.7 0.6 0.2 0 0 96 96.5 97 97.5 98 98.5 99 99.5 100 100.5 96.5 97 97.5 98 98.5 99 99.5 100 100.5 Sectio 13 Kolmogorov-Smirov test. Suppose that we have a i.i.d. sample X 1,..., X with some ukow distributio P ad we would like to test the hypothesis that P is equal to a particular distributio P 0, i.e.

More information

FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. 1. Powers of a matrix

FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. 1. Powers of a matrix FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. Powers of a matrix We begi with a propositio which illustrates the usefuless of the diagoalizatio. Recall that a square matrix A is diogaalizable if

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

3. Greatest Common Divisor - Least Common Multiple

3. Greatest Common Divisor - Least Common Multiple 3 Greatest Commo Divisor - Least Commo Multiple Defiitio 31: The greatest commo divisor of two atural umbers a ad b is the largest atural umber c which divides both a ad b We deote the greatest commo gcd

More information

2-3 The Remainder and Factor Theorems

2-3 The Remainder and Factor Theorems - The Remaider ad Factor Theorems Factor each polyomial completely usig the give factor ad log divisio 1 x + x x 60; x + So, x + x x 60 = (x + )(x x 15) Factorig the quadratic expressio yields x + x x

More information

S. Tanny MAT 344 Spring 1999. be the minimum number of moves required.

S. Tanny MAT 344 Spring 1999. be the minimum number of moves required. S. Tay MAT 344 Sprig 999 Recurrece Relatios Tower of Haoi Let T be the miimum umber of moves required. T 0 = 0, T = 7 Iitial Coditios * T = T + $ T is a sequece (f. o itegers). Solve for T? * is a recurrece,

More information

Gray level image enhancement using the Bernstein polynomials

Gray level image enhancement using the Bernstein polynomials Buletiul Ştiiţiic l Uiersităţii "Politehic" di Timişor Seri ELECTRONICĂ şi TELECOMUNICAŢII TRANSACTIONS o ELECTRONICS d COMMUNICATIONS Tom 47(6), Fscicol -, 00 Gry leel imge ehcemet usig the Berstei polyomils

More information

INVESTIGATION OF PARAMETERS OF ACCUMULATOR TRANSMISSION OF SELF- MOVING MACHINE

INVESTIGATION OF PARAMETERS OF ACCUMULATOR TRANSMISSION OF SELF- MOVING MACHINE ENGINEEING FO UL DEVELOENT Jelgv, 28.-29.05.2009. INVESTIGTION OF ETES OF CCUULTO TNSISSION OF SELF- OVING CHINE leksdrs Kirk Lithui Uiversity of griculture, Kus leksdrs.kirk@lzuu.lt.lt bstrct. Uder the

More information

CME 302: NUMERICAL LINEAR ALGEBRA FALL 2005/06 LECTURE 8

CME 302: NUMERICAL LINEAR ALGEBRA FALL 2005/06 LECTURE 8 CME 30: NUMERICAL LINEAR ALGEBRA FALL 005/06 LECTURE 8 GENE H GOLUB 1 Positive Defiite Matrices A matrix A is positive defiite if x Ax > 0 for all ozero x A positive defiite matrix has real ad positive

More information

Math 114- Intermediate Algebra Integral Exponents & Fractional Exponents (10 )

Math 114- Intermediate Algebra Integral Exponents & Fractional Exponents (10 ) Math 4 Math 4- Itermediate Algebra Itegral Epoets & Fractioal Epoets (0 ) Epoetial Fuctios Epoetial Fuctios ad Graphs I. Epoetial Fuctios The fuctio f ( ) a, where is a real umber, a 0, ad a, is called

More information

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008 I ite Sequeces Dr. Philippe B. Laval Keesaw State Uiversity October 9, 2008 Abstract This had out is a itroductio to i ite sequeces. mai de itios ad presets some elemetary results. It gives the I ite Sequeces

More information

THE REGRESSION MODEL IN MATRIX FORM. For simple linear regression, meaning one predictor, the model is. for i = 1, 2, 3,, n

THE REGRESSION MODEL IN MATRIX FORM. For simple linear regression, meaning one predictor, the model is. for i = 1, 2, 3,, n We will cosider the liear regressio model i matrix form. For simple liear regressio, meaig oe predictor, the model is i = + x i + ε i for i =,,,, This model icludes the assumptio that the ε i s are a sample

More information

m n Use technology to discover the rules for forms such as a a, various integer values of m and n and a fixed integer value a.

m n Use technology to discover the rules for forms such as a a, various integer values of m and n and a fixed integer value a. TIth.co Alger Expoet Rules ID: 988 Tie required 25 iutes Activity Overview This ctivity llows studets to work idepedetly to discover rules for workig with expoets, such s Multiplictio d Divisio of Like

More information

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem Lecture 4: Cauchy sequeces, Bolzao-Weierstrass, ad the Squeeze theorem The purpose of this lecture is more modest tha the previous oes. It is to state certai coditios uder which we are guarateed that limits

More information

Sequences and Series

Sequences and Series CHAPTER 9 Sequeces ad Series 9.. Covergece: Defiitio ad Examples Sequeces The purpose of this chapter is to itroduce a particular way of geeratig algorithms for fidig the values of fuctios defied by their

More information

Properties of MLE: consistency, asymptotic normality. Fisher information.

Properties of MLE: consistency, asymptotic normality. Fisher information. Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout

More information

n Using the formula we get a confidence interval of 80±1.64

n Using the formula we get a confidence interval of 80±1.64 9.52 The professor of sttistics oticed tht the rks i his course re orlly distributed. He hs lso oticed tht his orig clss verge is 73% with stdrd devitio of 12% o their fil exs. His fteroo clsses verge

More information

Lecture 5: Span, linear independence, bases, and dimension

Lecture 5: Span, linear independence, bases, and dimension Lecture 5: Spa, liear idepedece, bases, ad dimesio Travis Schedler Thurs, Sep 23, 2010 (versio: 9/21 9:55 PM) 1 Motivatio Motivatio To uderstad what it meas that R has dimesio oe, R 2 dimesio 2, etc.;

More information

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations CS3A Hadout 3 Witer 00 February, 00 Solvig Recurrece Relatios Itroductio A wide variety of recurrece problems occur i models. Some of these recurrece relatios ca be solved usig iteratio or some other ad

More information

GCE Further Mathematics (6360) Further Pure Unit 2 (MFP2) Textbook. Version: 1.4

GCE Further Mathematics (6360) Further Pure Unit 2 (MFP2) Textbook. Version: 1.4 GCE Further Mathematics (660) Further Pure Uit (MFP) Tetbook Versio: 4 MFP Tetbook A-level Further Mathematics 660 Further Pure : Cotets Chapter : Comple umbers 4 Itroductio 5 The geeral comple umber 5

More information

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions

Chapter 5 Unit 1. IET 350 Engineering Economics. Learning Objectives Chapter 5. Learning Objectives Unit 1. Annual Amount and Gradient Functions Chapter 5 Uit Aual Amout ad Gradiet Fuctios IET 350 Egieerig Ecoomics Learig Objectives Chapter 5 Upo completio of this chapter you should uderstad: Calculatig future values from aual amouts. Calculatig

More information

WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER?

WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER? WHEN IS THE (CO)SINE OF A RATIONAL ANGLE EQUAL TO A RATIONAL NUMBER? JÖRG JAHNEL 1. My Motivatio Some Sort of a Itroductio Last term I tought Topological Groups at the Göttige Georg August Uiversity. This

More information

SEQUENCES AND SERIES

SEQUENCES AND SERIES Chapter 9 SEQUENCES AND SERIES Natural umbers are the product of huma spirit. DEDEKIND 9.1 Itroductio I mathematics, the word, sequece is used i much the same way as it is i ordiary Eglish. Whe we say

More information

STUDY COURSE BACHELOR OF BUSINESS ADMINISTRATION (B.A.)

STUDY COURSE BACHELOR OF BUSINESS ADMINISTRATION (B.A.) STUDY COURSE BACHELOR OF BUSINESS ADMINISTRATION (B.A. MATHEMATICS (ENGLISH & GERMAN REPETITORIUM 0/06 Prof. Dr. Philipp E. Zeh Mthemtis Prof. Dr. Philipp E. Zeh LITERATURE (GERMAN Böker, F., Formelsmmlug

More information

4.3. The Integral and Comparison Tests

4.3. The Integral and Comparison Tests 4.3. THE INTEGRAL AND COMPARISON TESTS 9 4.3. The Itegral ad Compariso Tests 4.3.. The Itegral Test. Suppose f is a cotiuous, positive, decreasig fuctio o [, ), ad let a = f(). The the covergece or divergece

More information

Theorems About Power Series

Theorems About Power Series Physics 6A Witer 20 Theorems About Power Series Cosider a power series, f(x) = a x, () where the a are real coefficiets ad x is a real variable. There exists a real o-egative umber R, called the radius

More information

How To Solve The Homewor Problem Beautifully

How To Solve The Homewor Problem Beautifully Egieerig 33 eautiful Homewor et 3 of 7 Kuszmar roblem.5.5 large departmet store sells sport shirts i three sizes small, medium, ad large, three patters plaid, prit, ad stripe, ad two sleeve legths log

More information

Repeating Decimals are decimal numbers that have number(s) after the decimal point that repeat in a pattern.

Repeating Decimals are decimal numbers that have number(s) after the decimal point that repeat in a pattern. 5.5 Fractios ad Decimals Steps for Chagig a Fractio to a Decimal. Simplify the fractio, if possible. 2. Divide the umerator by the deomiator. d d Repeatig Decimals Repeatig Decimals are decimal umbers

More information

Cooley-Tukey. Tukey FFT Algorithms. FFT Algorithms. Cooley

Cooley-Tukey. Tukey FFT Algorithms. FFT Algorithms. Cooley Cooley Cooley-Tuey Tuey FFT Algorithms FFT Algorithms Cosider a legth- sequece x[ with a -poit DFT X[ where Represet the idices ad as +, +, Cooley Cooley-Tuey Tuey FFT Algorithms FFT Algorithms Usig these

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

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

Released Assessment Questions, 2015 QUESTIONS

Released Assessment Questions, 2015 QUESTIONS Relesed Assessmet Questios, 15 QUESTIONS Grde 9 Assessmet of Mthemtis Ademi Red the istrutios elow. Alog with this ooklet, mke sure you hve the Aswer Booklet d the Formul Sheet. You my use y spe i this

More information

Fast Fourier Transform

Fast Fourier Transform 18.310 lecture otes November 18, 2013 Fast Fourier Trasform Lecturer: Michel Goemas I these otes we defie the Discrete Fourier Trasform, ad give a method for computig it fast: the Fast Fourier Trasform.

More information

CS103X: Discrete Structures Homework 4 Solutions

CS103X: Discrete Structures Homework 4 Solutions CS103X: Discrete Structures Homewor 4 Solutios Due February 22, 2008 Exercise 1 10 poits. Silico Valley questios: a How may possible six-figure salaries i whole dollar amouts are there that cotai at least

More information

Asymptotic Growth of Functions

Asymptotic Growth of Functions CMPS Itroductio to Aalysis of Algorithms Fall 3 Asymptotic Growth of Fuctios We itroduce several types of asymptotic otatio which are used to compare the performace ad efficiecy of algorithms As we ll

More information

Convexity, Inequalities, and Norms

Convexity, Inequalities, and Norms Covexity, Iequalities, ad Norms Covex Fuctios You are probably familiar with the otio of cocavity of fuctios. Give a twicedifferetiable fuctio ϕ: R R, We say that ϕ is covex (or cocave up) if ϕ (x) 0 for

More information

Factors of sums of powers of binomial coefficients

Factors of sums of powers of binomial coefficients ACTA ARITHMETICA LXXXVI.1 (1998) Factors of sums of powers of biomial coefficiets by Neil J. Cali (Clemso, S.C.) Dedicated to the memory of Paul Erdős 1. Itroductio. It is well ow that if ( ) a f,a = the

More information

1 Computing the Standard Deviation of Sample Means

1 Computing the Standard Deviation of Sample Means Computig the Stadard Deviatio of Sample Meas Quality cotrol charts are based o sample meas ot o idividual values withi a sample. A sample is a group of items, which are cosidered all together for our aalysis.

More information

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth Questio 1: What is a ordiary auity? Let s look at a ordiary auity that is certai ad simple. By this, we mea a auity over a fixed term whose paymet period matches the iterest coversio period. Additioally,

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

I. Chi-squared Distributions

I. Chi-squared Distributions 1 M 358K Supplemet to Chapter 23: CHI-SQUARED DISTRIBUTIONS, T-DISTRIBUTIONS, AND DEGREES OF FREEDOM To uderstad t-distributios, we first eed to look at aother family of distributios, the chi-squared distributios.

More information

We will begin this chapter with a quick refresher of what an exponent is.

We will begin this chapter with a quick refresher of what an exponent is. .1 Exoets We will egi this chter with quick refresher of wht exoet is. Recll: So, exoet is how we rereset reeted ultilictio. We wt to tke closer look t the exoet. We will egi with wht the roerties re for

More information

Approximating Area under a curve with rectangles. To find the area under a curve we approximate the area using rectangles and then use limits to find

Approximating Area under a curve with rectangles. To find the area under a curve we approximate the area using rectangles and then use limits to find 1.8 Approximatig Area uder a curve with rectagles 1.6 To fid the area uder a curve we approximate the area usig rectagles ad the use limits to fid 1.4 the area. Example 1 Suppose we wat to estimate 1.

More information

Normal Distribution.

Normal Distribution. Normal Distributio www.icrf.l Normal distributio I probability theory, the ormal or Gaussia distributio, is a cotiuous probability distributio that is ofte used as a first approimatio to describe realvalued

More information

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009)

Lecture 13. Lecturer: Jonathan Kelner Scribe: Jonathan Pines (2009) 18.409 A Algorithmist s Toolkit October 27, 2009 Lecture 13 Lecturer: Joatha Keler Scribe: Joatha Pies (2009) 1 Outlie Last time, we proved the Bru-Mikowski iequality for boxes. Today we ll go over the

More information

Chapter 5 O A Cojecture Of Erdíos Proceedigs NCUR VIII è1994è, Vol II, pp 794í798 Jeærey F Gold Departmet of Mathematics, Departmet of Physics Uiversity of Utah Do H Tucker Departmet of Mathematics Uiversity

More information

Section 8.3 : De Moivre s Theorem and Applications

Section 8.3 : De Moivre s Theorem and Applications The Sectio 8 : De Moivre s Theorem ad Applicatios Let z 1 ad z be complex umbers, where z 1 = r 1, z = r, arg(z 1 ) = θ 1, arg(z ) = θ z 1 = r 1 (cos θ 1 + i si θ 1 ) z = r (cos θ + i si θ ) ad z 1 z =

More information

Permutations, the Parity Theorem, and Determinants

Permutations, the Parity Theorem, and Determinants 1 Permutatios, the Parity Theorem, ad Determiats Joh A. Guber Departmet of Electrical ad Computer Egieerig Uiversity of Wiscosi Madiso Cotets 1 What is a Permutatio 1 2 Cycles 2 2.1 Traspositios 4 3 Orbits

More information

MATH 150 HOMEWORK 4 SOLUTIONS

MATH 150 HOMEWORK 4 SOLUTIONS MATH 150 HOMEWORK 4 SOLUTIONS Section 1.8 Show tht the product of two of the numbers 65 1000 8 2001 + 3 177, 79 1212 9 2399 + 2 2001, nd 24 4493 5 8192 + 7 1777 is nonnegtive. Is your proof constructive

More information

Department of Computer Science, University of Otago

Department of Computer Science, University of Otago Departmet of Computer Sciece, Uiversity of Otago Techical Report OUCS-2006-09 Permutatios Cotaiig May Patters Authors: M.H. Albert Departmet of Computer Sciece, Uiversity of Otago Micah Colema, Rya Fly

More information

1 Correlation and Regression Analysis

1 Correlation and Regression Analysis 1 Correlatio ad Regressio Aalysis I this sectio we will be ivestigatig the relatioship betwee two cotiuous variable, such as height ad weight, the cocetratio of a ijected drug ad heart rate, or the cosumptio

More information

How To Solve An Old Japanese Geometry Problem

How To Solve An Old Japanese Geometry Problem 116 Taget circles i the ratio 2 : 1 Hiroshi Okumura ad Masayuki Wataabe I this article we cosider the followig old Japaese geometry problem (see Figure 1), whose statemet i [1, p. 39] is missig the coditio

More information

Basic Elements of Arithmetic Sequences and Series

Basic Elements of Arithmetic Sequences and Series MA40S PRE-CALCULUS UNIT G GEOMETRIC SEQUENCES CLASS NOTES (COMPLETED NO NEED TO COPY NOTES FROM OVERHEAD) Basic Elemets of Arithmetic Sequeces ad Series Objective: To establish basic elemets of arithmetic

More information

PREMIUMS CALCULATION FOR LIFE INSURANCE

PREMIUMS CALCULATION FOR LIFE INSURANCE ls of the Uiversity of etroşi, Ecoomics, 2(3), 202, 97-204 97 REIUS CLCULTIO FOR LIFE ISURCE RE, RI GÎRBCI * BSTRCT: The pper presets the techiques d the formuls used o itertiol prctice for estblishig

More information

Present and future value formulae for uneven cash flow Based on performance of a Business

Present and future value formulae for uneven cash flow Based on performance of a Business Advces i Mgemet & Applied Ecoomics, vol., o., 20, 93-09 ISSN: 792-7544 (prit versio), 792-7552 (olie) Itertiol Scietific Press, 20 Preset d future vlue formule for ueve csh flow Bsed o performce of Busiess

More information

3 Basic Definitions of Probability Theory

3 Basic Definitions of Probability Theory 3 Basic Defiitios of Probability Theory 3defprob.tex: Feb 10, 2003 Classical probability Frequecy probability axiomatic probability Historical developemet: Classical Frequecy Axiomatic The Axiomatic defiitio

More information

Heat (or Diffusion) equation in 1D*

Heat (or Diffusion) equation in 1D* Heat (or Diffusio) equatio i D* Derivatio of the D heat equatio Separatio of variables (refresher) Worked eamples *Kreysig, 8 th Ed, Sectios.4b Physical assumptios We cosider temperature i a log thi wire

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

Partial Di erential Equations

Partial Di erential Equations Partial Di eretial Equatios Partial Di eretial Equatios Much of moder sciece, egieerig, ad mathematics is based o the study of partial di eretial equatios, where a partial di eretial equatio is a equatio

More information

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have

Complex Numbers. where x represents a root of Equation 1. Note that the ± sign tells us that quadratic equations will have Comple Numbers I spite of Calvi s discomfiture, imagiar umbers (a subset of the set of comple umbers) eist ad are ivaluable i mathematics, egieerig, ad sciece. I fact, i certai fields, such as electrical

More information

Your organization has a Class B IP address of 166.144.0.0 Before you implement subnetting, the Network ID and Host ID are divided as follows:

Your organization has a Class B IP address of 166.144.0.0 Before you implement subnetting, the Network ID and Host ID are divided as follows: Subettig Subettig is used to subdivide a sigle class of etwork i to multiple smaller etworks. Example: Your orgaizatio has a Class B IP address of 166.144.0.0 Before you implemet subettig, the Network

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

Review: Classification Outline

Review: Classification Outline Data Miig CS 341, Sprig 2007 Decisio Trees Neural etworks Review: Lecture 6: Classificatio issues, regressio, bayesia classificatio Pretice Hall 2 Data Miig Core Techiques Classificatio Clusterig Associatio

More information

Chapter 7 - Sampling Distributions. 1 Introduction. What is statistics? It consist of three major areas:

Chapter 7 - Sampling Distributions. 1 Introduction. What is statistics? It consist of three major areas: Chapter 7 - Samplig Distributios 1 Itroductio What is statistics? It cosist of three major areas: Data Collectio: samplig plas ad experimetal desigs Descriptive Statistics: umerical ad graphical summaries

More information

Lecture 4: Cheeger s Inequality

Lecture 4: Cheeger s Inequality Spectral Graph Theory ad Applicatios WS 0/0 Lecture 4: Cheeger s Iequality Lecturer: Thomas Sauerwald & He Su Statemet of Cheeger s Iequality I this lecture we assume for simplicity that G is a d-regular

More information

Definition. A variable X that takes on values X 1, X 2, X 3,...X k with respective frequencies f 1, f 2, f 3,...f k has mean

Definition. A variable X that takes on values X 1, X 2, X 3,...X k with respective frequencies f 1, f 2, f 3,...f k has mean 1 Social Studies 201 October 13, 2004 Note: The examples i these otes may be differet tha used i class. However, the examples are similar ad the methods used are idetical to what was preseted i class.

More information

AP Calculus AB 2006 Scoring Guidelines Form B

AP Calculus AB 2006 Scoring Guidelines Form B AP Calculus AB 6 Scorig Guidelies Form B The College Board: Coectig Studets to College Success The College Board is a ot-for-profit membership associatio whose missio is to coect studets to college success

More information

CHAPTER 3 THE TIME VALUE OF MONEY

CHAPTER 3 THE TIME VALUE OF MONEY CHAPTER 3 THE TIME VALUE OF MONEY OVERVIEW A dollar i the had today is worth more tha a dollar to be received i the future because, if you had it ow, you could ivest that dollar ad ear iterest. Of all

More information

Find the inverse Laplace transform of the function F (p) = Evaluating the residues at the four simple poles, we find. residue at z = 1 is 4te t

Find the inverse Laplace transform of the function F (p) = Evaluating the residues at the four simple poles, we find. residue at z = 1 is 4te t Homework Solutios. Chater, Sectio 7, Problem 56. Fid the iverse Lalace trasform of the fuctio F () (7.6). À Chater, Sectio 7, Problem 6. Fid the iverse Lalace trasform of the fuctio F () usig (7.6). Solutio:

More information

Authorized licensed use limited to: University of Illinois. Downloaded on July 27,2010 at 06:52:39 UTC from IEEE Xplore. Restrictions apply.

Authorized licensed use limited to: University of Illinois. Downloaded on July 27,2010 at 06:52:39 UTC from IEEE Xplore. Restrictions apply. Uiversl Dt Compressio d Lier Predictio Meir Feder d Adrew C. Siger y Jury, 998 The reltioship betwee predictio d dt compressio c be exteded to uiversl predictio schemes d uiversl dt compressio. Recet work

More information

The following example will help us understand The Sampling Distribution of the Mean. C1 C2 C3 C4 C5 50 miles 84 miles 38 miles 120 miles 48 miles

The following example will help us understand The Sampling Distribution of the Mean. C1 C2 C3 C4 C5 50 miles 84 miles 38 miles 120 miles 48 miles The followig eample will help us uderstad The Samplig Distributio of the Mea Review: The populatio is the etire collectio of all idividuals or objects of iterest The sample is the portio of the populatio

More information

MATHEMATICAL INDUCTION

MATHEMATICAL INDUCTION MATHEMATICAL INDUCTION. Itroductio Mthemtics distiguishes itself from the other scieces i tht it is built upo set of xioms d defiitios, o which ll subsequet theorems rely. All theorems c be derived, or

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

4.11 Inner Product Spaces

4.11 Inner Product Spaces 314 CHAPTER 4 Vector Spces 9. A mtrix of the form 0 0 b c 0 d 0 0 e 0 f g 0 h 0 cnnot be invertible. 10. A mtrix of the form bc d e f ghi such tht e bd = 0 cnnot be invertible. 4.11 Inner Product Spces

More information

Math 113 HW #11 Solutions

Math 113 HW #11 Solutions Math 3 HW # Solutios 5. 4. (a) Estimate the area uder the graph of f(x) = x from x = to x = 4 usig four approximatig rectagles ad right edpoits. Sketch the graph ad the rectagles. Is your estimate a uderestimate

More information

MODULE 3. 0, y = 0 for all y

MODULE 3. 0, y = 0 for all y Topics: Inner products MOULE 3 The inner product of two vectors: The inner product of two vectors x, y V, denoted by x, y is (in generl) complex vlued function which hs the following four properties: i)

More information