信号与系统奥本海姆英文版课后答案chapter8
[信号与系统][第二版][奥本海姆][课后答案][英文][文字版]
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Signals & Systems
(Second Edition)
—Learning Instructions
(Exercises Answers)
Department of Computer Engineering 2005.12
Contents
Chapter 1 ······················································· 2 Chapter 2 ······················································· 17 Chapter 3 ······················································· 35 Chapter 4 ······················································· 62 Chapter 5 ······················································· 83 Chapter 6 ······················································· 109 Chapter 7 ······················································· 119 Chapter 8 ······················································· 132 Chapter 9 ······················································· 140 Chapter 10 ·······················································160
信号与系统奥本海姆原版PPT第八章
For convenience, choose c=0, so y(t ) x(t )c(t ) x(t ) cos ct
1 Y ( j ) X ( j ) * C ( j ) 2 C ( j ) ( c ) ( c ) Y ( j ) 1 1 X ( j j c ) X ( j j c ) 2 2
x(t) --- modulating signal c(t) --- Carrier signal
8 Communication systems
8.1.1 Amplitude Modulation with Complex Exponential Carrier (1) Modulation Theory Exponential carrier:
The output of lowpass filter:
x(t ) cos( c c )
Ideal output: x(t) ( c c is desired ) When c c , it is referred to as synchronous demodulation.
8 Communication systems
8 Communication systems
8 Communication systems
8.2 Demodulation for Sinusoidal AM 8.2.1 Synchronous demodulation (1) Demodulation process
8 Communication systems
In time dom c t 1 1 x(t ) x(t ) cos 2 c t 2 2
In frequency domain:
奥本海姆版信号与系统课后答案
第七章7.6 解：见 8.17.8 解： (a) )]()([)21()(50πωδπωδπωk k j j X n k +--=∑= 信号截止频率 πω5=m采样频率 m s T ωπππω2102.022====对于正弦信号，会发生混叠 (b) ππω5==T c所以输出信号 )sin()21()(40t k t y k k π∑== 所以j e e t g tjk t jk k k 2)21()(40ππ-=-=∑ ∑-==44k t jk k e a π其中，⎪⎪⎩⎪⎪⎨⎧≤≤-=≤≤-=+-+14)21(0041)21(11k j k k j a k k k 7.10 解：(a) 错 信号时域为矩形波，频域为sinc 函数，无论怎么样都会混叠 (b) 符合采样定理，对(c) 符合采样定理，对7.15 解：要求 76N 2,76273ππππω>=⨯>即s 237max =<∴N N 取 7.16 解： 易见ππn n 2sin2满足性质1, 3对性质2，考虑时域乘积得频域卷积，易见2))2/sin((4][n n n x ππ=7.19 解：设x[n]经零值插入后得输出为z[n] (a) 531πω≤时， ⎪⎩⎪⎨⎧><=1101)(ωωωωωj e X ⎪⎪⎩⎪⎪⎨⎧>≤<=30531)(11ωωπωωωj e Z所以 ⎪⎪⎩⎪⎪⎨⎧><=3031)(11ωωωωωj e W因此可得，n n n w πω/)3(sin ][1=又由 ]5[][n w n y =可得 )5/()35(sin][1n n n y πω= (b) 531πω>时 ⎪⎪⎩⎪⎪⎨⎧>><=53031)(11πωωωωωj e Z)/()5(sin ][n nn w ππ=∴][51)5/()(sin ][n n n n y δππ== 7.21 解： 采样频率m s Tωππω2200002>== 即πω10000<m 时，可以恢复 (a) 可以(b) 不可以(c) 不能确定(d) 可以 (e) 不可以 (f) 可以 (g) 可以7.22 解：)(*)()(21t x t x t y = 则有πωωωω10000)()()(21>==j X j X j Y πω1000=∴m 因而 πωω20002=>m s故 s T s 3102-=<ωπ 7.23 解：见 8.27.24 解：见 8.37.29 解：见 8.107.31 解：见 8.157.35 解：见 8.247.38 解：见 8.97.41 解：见 8.197.45 解： 见 8.17。
英文版《信号与系统》第六七八章习题解答
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奥本海姆 信号与系统 习题参考答案 电子科技大学
Chapter 22.1 Solution:Because x[n]=(1 2 0 –1)0, h[n]=(2 0 2)1-, then (a).So, ]4[2]2[2]1[2][4]1[2][1---+-+++=n n n n n n y δδδδδ(b). according to the property of convolutioin:]2[][12+=n y n y(c). ]2[][13+=n y n y2.3 Solution:][*][][n h n x n y =][][k n h k x k -=∑∞-∞=∑∞-∞=-+--=k k k n u k u ]2[]2[)21(2][211)21()21(][)21(12)2(0222n u n u n n k k --==+-++=-∑][])21(1[21n u n +-=the figure of the y[n] is:2.5 Solution:We have known: ⎩⎨⎧≤≤=elsewhere n n x ....090....1][，，, ⎩⎨⎧≤≤=elsewhere N n n h ....00....1][，，,(9≤N)Then, ]10[][][--=n u n u n x , ]1[][][---=N n u n u n h∑∞-∞=-==k k n u k h n h n x n y ][][][*][][∑∞-∞=-------=k k n u k n u N k u k u ])10[][])(1[][(So, y[4] ∑∞-∞=-------=k k u k u N k u k u ])6[]4[])(1[][(⎪⎪⎩⎪⎪⎨⎧≥≤=∑∑==4,...14, (14)N N k Nk =5, then 4≥NAnd y[14] ∑∞-∞=------=k k u k u N k u k u ])4[]14[])(1[][(⎪⎪⎩⎪⎪⎨⎧≥≤=∑∑==14,...114, (114)55N N k Nk =0, then 5<N∴ 4=N2.7 Solution:[][][2]k y n x k g n k ∞=-∞=-∑（a ） [][1]x n n δ=-,[][][2][1][2][2]k k y n x k g n k k g n k g n δ∞∞=-∞=-∞=-=--=-∑∑(b) [][2]x n n δ=-,[][][2][2][2][4]k k y n x k g n k k g n k g n δ∞∞=-∞=-∞=-=--=-∑∑(c) S is not LTI system.. (d) [][]x n u n =,0[][][2][][2][2]k k k y n x k g n k u k g n k g n k ∞∞∞=-∞=-∞==-=-=-∑∑∑2.8 Solution:)]1(2)2([*)()(*)()(+++==t t t x t h t x t y δδ)1(2)2(+++=t x t xThen,That is, ⎪⎪⎪⎩⎪⎪⎪⎨⎧≤<-≤<-+-=-<<-+=others t t t t t t t t y ,........010,....2201,.....41..,.........412,.....3)(2.10 Solution:(a). We know: Then, )()()(αδδ--='t t t h)]()([*)()(*)()(αδδ--='='t t t x t h t x t y)()(α--=t x t xthat is,So, ⎪⎪⎩⎪⎪⎨⎧+≤≤-+≤≤≤≤=others t t t t t t y ,.....011,.....11,....0,.....)(ααααα(b). From the figure of )(t y ', only if 1=α, )(t y ' would contain merely therediscontinuities.2.11 Solution:(a). )(*)]5()3([)(*)()(3t u e t u t u t h t x t y t ----==⎰⎰∞∞---∞∞--------=ττττττττd t u e u d t u eu t t )()5()()3()(3)(3⎰⎰-------=tt t t d e t u d et u 5)(33)(3)5()3(ττττ⎪⎪⎪⎪⎩⎪⎪⎪⎪⎨⎧≥+-=-<≤-=<=---------⎰⎰⎰5,.......353,.....313.........,.........0315395)(33)(3393)(3t e e d e d e t e d e t tt t t t t t t t ττττττ(b). )(*)]5()3([)(*)/)(()(3t u e t t t h dt t dx t g t----==δδ)5()3()5(3)3(3---=----t u e t u e t t(c). It ’s obvious that dt t dy t g /)()(=.2.12 Solution∑∑∞-∞=-∞-∞=--=-=k tk tk t t u ek t t u e t y )]3(*)([)3(*)()(δδ∑∞-∞=---=k k t k t u e)3()3(Considering for 30<≤t ,we can obtain33311])3([)(---∞=-∞-∞=--==-=∑∑e e e ek t u e e t y tk k tk kt.(Because k must be negetive , 1)3(=-k t u for 30<≤t ).2.19 Solution:(a). We have known: ][]1[21][n x n w n w +-=(1)][]1[][n w n y n y βα+-=(2)from (1), 21)(1-=E EE Hfrom (2), αβ-=E EE H )(2then, 212212)21(1)21)(()()()(--++-=--==E E E E E E H E H E H ααβαβ∴ ][]2[2]1[)21(][n x n y n y n y βαα=-+-+-but, ][]1[43]2[81][n x n y n y n y +-+--=∴ ⎪⎩⎪⎨⎧=⎪⎭⎫ ⎝⎛=+=143)21(:....812βααor∴⎪⎩⎪⎨⎧==141βα (b). from (a), we know )21)(41()()()(221--==E E E E H E H E H21241-+--=E E E E∴ ][)41()21(2][n u n h n n ⎥⎦⎤⎢⎣⎡-=2.20 (a). 1⎰⎰∞∞-∞∞-===1)0cos()cos()()cos()(0dt t t dt t t u δ(b). 0 dt t t )3()2sin(5+⎰δπ has value only on 3-=t , but ]5,0[3∉-∴dt t t )3()2sin(5+⎰δπ=0(c). 0⎰⎰---=-641551)2cos()()2cos()1(dt t t u d u πτπττ⎰-'-=64)2cos()(dt t t πδ0|)2(s co ='=t t π0|)2sin(20=-==t t ππ2.23 Solution:∑∞-∞=-==k t h kT t t h t x t y )(*)()(*)()(δ∑∞-∞=-=k kT t h )(∴2.27 Solution()y A y t dt ∞-∞=⎰,()xA x t dt ∞-∞=⎰,()hA h t dt ∞-∞=⎰.()()*()()()y t x t h t x x t d τττ∞-∞==-⎰()()()()()()()()()(){()}y x hA y t dt x x t d dtx x t dtd x x t dtd x x d d x d x d A A ττττττττττξξτττξξ∞∞∞-∞-∞-∞∞∞∞∞-∞-∞-∞-∞∞∞∞∞-∞-∞-∞-∞==-=-=-===⎰⎰⎰⎰⎰⎰⎰⎰⎰⎰⎰2.40 Solution(a) ()()(2)tt y t ex d τττ---∞=-⎰,Let ()()x t t δ=,then ()()y t h t =.So , 2()(2)(2)()(2)()(2)tt t t t h t ed e d e u t τξδττδξξ---------∞-∞=-==-⎰⎰(b) (2)()()*()[(1)(2)]*(2)t y t x t h t u t u t eu t --==+---(2)(2)(1)(2)(2)(2)t t u eu t d u e u t d ττττττττ∞∞-------∞-∞=+------⎰⎰22(2)(2)12(1)(4)t t t t u t ed u te d ττττ---------=---⎰⎰(2)2(2)212(1)[]|(4)[]|t t t t u t e e u t ee ττ-------=--- (1)(4)[1](1)[1](4)t t e u t e u t ----=-----2.46 SolutionBecause)]1([2)1(]2[)(33-+-=--t u dtde t u e dt d t x dt d t t)1(2)(3)1(2)(333-+-=-+-=--t e t x t et x tδδ.From LTI property ,we know)1(2)(3)(3-+-→-t h e t y t x dtdwhere )(t h is the impulse response of the system. So ,following equation can be derived.)()1(223t u e t h e t --=-Finally, )1(21)()1(23+=+-t u e e t h t 2.47 SoliutionAccording to the property of the linear time-invariant system: (a). )(2)(*)(2)(*)()(000t y t h t x t h t x t y ===(b). )(*)]2()([)(*)()(00t h t x t x t h t x t y --==)(*)2()(*)(0000t h t x t h t x --=)2()(00--=t y t y(c). )1()1(*)(*)2()1(*)2()(*)()(00000-=+-=+-==t y t t h t x t h t x t h t x t y δ(d). The condition is not enough.(e). )(*)()(*)()(00t h t x t h t x t y --== τττd t h x )()(00+--=⎰∞∞-)()()(000t y dm m t h m x -=--=⎰∞∞-(f). )()]([)](*)([)(*)()(*)()(000000t y t y t h t x t h t x t h t x t y "=''='--'=-'-'==Extra problems:1. Solute h(t), h[n](1). )()(6)(5)(22t x t y t y dt dt y dtd =++ (2). ]1[][2]1[2]2[+=++++n x n y n y n y012y(t)t4Solution:(1). Because 3121)3)(2(1651)(2+-++=++=++=P P P P P P P H so )()()()3121()(32t u e e t P P t h t t ---=+-++=δ (2). Because )1)(1(1)1(22)(22i E i E EE E E E E E H -+++=++=++=iE Ei i E E i -+-+++=1212so []][)1()1(2][1212][n u i i i k i E E i i E E i n h n n +----=⎪⎪⎪⎪⎭⎫⎝⎛-+-+++=δ。
信号与系统奥本海姆英文版课后问题详解chapter1
实用标准Chapter 1 Answers1.1 Converting from polar to Cartesian coordinates:111cos 222j e ππ==-111c o s ()222j e ππ-=-=- 2cos()sin()22jj j eπππ=+=2c o s ()s i n ()22jjj eπππ-=-=- 522j jj eeππ==4c o s ()s i n ())144jjj πππ=+=+9441j jj ππ=-9441j j j ππ--=-41jj π-=-1.2 055j=, 22j e π-=,233jj eπ--=212jeπ--=, 41j j π+=, ()2221jj eπ-=-4(1)j je π-=, 411j jeπ+=-12e π-= 1.3. (a) E ∞=4014tdt e∞-=⎰, P ∞=0, because E ∞<∞ (b) (2)42()j t t x eπ+=, 2()1t x =.Therefore, E ∞=22()dt t x +∞-∞⎰=dt +∞-∞⎰=∞,P ∞=211lim lim222()TTTTT T dt dt T Tt x --→∞→∞==⎰⎰lim11T →∞=(c) 2()t x =cos(t). Therefore, E ∞=23()dt t x +∞-∞⎰=2cos()dt t +∞-∞⎰=∞,P ∞=2111(2)1lim lim 2222cos()TTTT T T COS t dt dt T Tt --→∞→∞+==⎰⎰(d)1[][]12nn u n x =⎛⎫ ⎪⎝⎭,2[]11[]4nu n n x =⎛⎫ ⎪⎝⎭. Therefore, E ∞=24131[]4nn n x +∞∞-∞===⎛⎫∑∑ ⎪⎝⎭P ∞=0，because E ∞<∞.(e) 2[]n x =()28n j e ππ-+, 22[]n x=1. therefore, E ∞=22[]n x +∞-∞∑=∞,P ∞=211limlim1122121[]NNN N n Nn NN N n x →∞→∞=-=-==++∑∑.(f) 3[]n x =cos 4nπ⎛⎫ ⎪⎝⎭. Therefore, E ∞=23[]n x +∞-∞∑=2cos()4n π+∞-∞∑=2cos()4n π+∞-∞∑,P ∞=1limcos 214nNN n NN π→∞=-=+⎛⎫∑ ⎪⎝⎭1cos()112lim ()2122NN n Nn N π→∞=-+=+∑ 1.4. (a) The signal x[n] is shifted by 3 to the right. The shifted signal will be zero for n<1, And n>7. (b) The signal x[n] is shifted by 4 to the left. The shifted signal will be zero for n<-6. And n>0. (c) The signal x[n] is flipped signal will be zero for n<-1 and n>2.(d) The signal x[n] is flipped and the flipped signal is shifted by 2 to the right. The new Signal will be zero for n<-2 and n>4.(e) The signal x[n] is flipped and the flipped and the flipped signal is shifted by 2 to the left. This new signal will be zero for n<-6 and n>0.1.5. (a) x(1-t) is obtained by flipping x(t) and shifting the flipped signal by 1 to the right. Therefore, x (1-t) will be zero for t>-2. (b) From (a), we know that x(1-t) is zero for t>-2. Similarly, x(2-t) is zero for t>-1, Therefore, x (1-t) +x(2-t) will be zero for t>-2. (c) x(3t) is obtained by linearly compression x(t) by a factor of3. Therefore, x(3t) will be zero for t<1.(d) x(t/3) is obtained by linearly compression x(t) by a factor of 3. Therefore, x(3t) will bezero for t<9.1.6(a) x1(t) is not periodic because it is zero for t<0.(b) x2[n]=1 for all n. Therefore, it is periodic with a fundamental period of 1.(c) x3[n1.7. (a)()1[]vnxε={}1111[][]([][4][][4])22n n u n u n u n u nx x+-=--+----Therefore, ()1[]vnxεis zero for1[]nx>3.(b) Since x1(t) is an odd signal, ()2[]vnxεis zero for all values of t.(c)(){}11311[][][][3][3]221122vn nn n n u n u nx x xε-⎡⎤⎢⎥=+-=----⎢⎥⎢⎥⎣⎦⎛⎫⎛⎫⎪ ⎪⎝⎭⎝⎭Therefore, ()3[]vnxεis zero when n<3 and when n→∞.(d) ()1554411()(()())(2)(2)22vt tt t t u t u tx x x e eε-⎡⎤=+-=---+⎣⎦Therefore, ()4()vtxεis zero only when t→∞.1.8. (a) ()01{()}22cos(0)tt tx eπℜ=-=+(b) ()02{()}cos()cos(32)cos(3)cos(30)4tt t t tx eππℜ=+==+(c) ()3{()}sin(3)sin(3)2t tt t tx e eππ--ℜ=+=+(d) ()224{()}sin(100)sin(100)cos(100)2t t tt t t tx e e eππ---ℜ=-=+=+1.9. (a)1()tx is a periodic complex exponential.101021()j t j tt jx e eπ⎛⎫+⎪⎝⎭==(b)2()tx is a complex exponential multiplied by a decaying exponential. Therefore,2()tx is not periodic.（c）3[]nx is a periodic signal. 3[]n x=7j neπ=j neπ.3[]nx is a complex exponential with a fundamental period of 22ππ=.(d)4[]nx is a periodic signal. The fundamental period is given by N=m(23/5ππ)=10().3mBy choosing m=3. We obtain the fundamental period to be 10.(e)5[]nx is not periodic. 5[]nx is a complex exponential with 0w=3/5. We cannot find any integer m such that m(2wπ) is also an integer. Therefore,5[]nxis not periodic.1.10. x(t)=2cos(10t＋1)-sin(4t-1)Period of first term in the RHS =2105ππ=.Period of first term in the RHS =242ππ=.Therefore, the overall signal is periodic with a period which the least commonmultiple of the periods of the first and second terms. This is equal toπ.1.11. x[n] = 1+74j n e π−25j n e πPeriod of first term in the RHS =1. Period of second term in the RHS =⎪⎭⎫ ⎝⎛7/42π=7 （when m=2）Period of second term in the RHS =⎪⎭⎫ ⎝⎛5/22ππ=5 (when m=1)Therefore, the overall signal x[n] is periodic with a period which is the least common Multiple of the periods of the three terms inn x[n].This is equal to 35.1.12. The signal x[n] is as shown in figure S1.12. x[n] can be obtained by flipping u[n] and thenShifting the flipped signal by 3 to the right. Therefore, x[n]=u[-n+3]. This implies that M=-1 and no=-3.1.13y (t)=⎰∞-tdt x )(τ =dt t))2()2((--+⎰∞-τδτδ=⎪⎩⎪⎨⎧>≤≤--<2,022,12,0,t t tTherefore ⎰-==∞224dt E∑∑∞-∞=∞-∞=----=k k k t k t t g 12(3)2(3)(δδ)This implies that A 1=3, t 1=0, A 2=-3, and t 2=1.1.15 (a) The signal x 2[n], which is the input to S 2, is the same as y 1[n].Therefore ,y 2[n]= x 2[n-2]+21x 2[n-3] = y 1[n-2]+ 21y 1[n-3]=2x 1[n-2] +4x 1[n-3] +21( 2x 1[n-3]+ 4x 1[n-4]) =2x 1[n-2]+ 5x 1[n-3] + 2x 1[n-4] The input-output relationship for S isy[n]=2x[n-2]+ 5x [n-3] + 2x [n-4](b) The input-output relationship does not change if the order in which S 1and S 2 are connected series reversed. . We can easily prove this assuming that S 1 follows S 2. In this case , the signal x 1[n], which is the input to S 1 is the same as y 2[n].Therefore y 1[n] =2x 1[n]+ 4x 1[n-1]= 2y 2[n]+4 y 2[n-1]=2( x 2[n-2]+21 x 2[n-3] )+4(x 2[n-3]+21x 2[n-4]) =2 x 2[n-2]+5x 2[n-3]+ 2 x 2[n-4]The input-output relationship for S is once againy[n]=2x[n-2]+ 5x [n-3] + 2x [n-4]1.16 (a)The system is not memory less because y[n] depends on past values of x[n].(b)The output of the system will be y[n]= ]2[][-n n δδ=0(c)From the result of part (b), we may conclude that the system output is always zero for inputs of the form ][k n -δ, k ∈ ґ. Therefore , the system is not invertible .1.17 (a) The system is not causal because the output y(t) at some time may depend on future values of x(t). For instance , y(-π)=x(0).(b) Consider two arbitrary inputs x 1(t)and x 2(t).x 1(t) →y 1(t)= x 1(sin(t)) x 2(t) → y 2(t)= x 2(sin(t))Let x 3(t) be a linear combination of x 1(t) and x 2(t).That is , x 3(t)=a x 1(t)+b x 2(t)Where a and b are arbitrary scalars .If x 3(t) is the input to the given system ,then the corresponding output y 3(t) is y 3(t)= x 3( sin(t))=a x 1(sin(t))+ x 2(sin(t)) =a y 1(t)+ by 2(t)Therefore , the system is linear.1.18.(a) Consider two arbitrary inputs x 1[n]and x 2[n].x 1[n] → y 1[n] =][001k x n n n n k ∑+-=x 2[n ] → y 2[n] =][02k x n n n n k ∑+-=Let x 3[n] be a linear combination of x 1[n] and x 2[n]. That is :x 3[n]= ax 1[n]+b x 2[n]where a and b are arbitrary scalars. If x 3[n] is the input to the given system, then the corresponding outputy 3[n] is y 3[n]=][03k x n n n n k ∑+-==])[][(2100k bx k ax n n n n k +∑+-==a ][001k x n n n n k ∑+-=+b ][02k x n n n n k ∑+-== ay 1[n]+b y 2[n]Therefore the system is linear.(b) Consider an arbitrary input x 1[n].Lety 1[n] =][01k x n n n n k ∑+-=be the corresponding output .Consider a second input x 2[n] obtained by shifting x 1[n] in time:x 2[n]= x 1[n-n 1]The output corresponding to this input isy 2[n]=][02k x n n n n k ∑+-== ]n [1100-∑+-=k x n n n n k = ][01011k x n n n n n n k ∑+---=Also note that y 1[n- n 1]=][01011k x n n n n n n k ∑+---=.Therefore , y 2[n]= y 1[n- n 1] This implies that the system is time-invariant.(c) If ][n x <B, then y[n]≤(2 n 0+1)B. Therefore ,C ≤(2 n 0+1)B.1.19 (a) (i) Consider two arbitrary inputs x 1(t) and x 2(t). x 1(t) → y 1(t)= t 2x 1(t-1)x 2(t) → y 2(t)= t 2x 2(t-1)Let x 3(t) be a linear combination of x 1(t) and x 2(t).That is x 3(t)=a x 1(t)+b x 2(t)where a and b are arbitrary scalars. If x 3(t) is the input to the given system, then the corresponding output y 3(t) is y 3(t)= t 2x 3 (t-1)= t 2(ax 1(t-1)+b x 2(t-1))= ay 1(t)+b y 2(t)Therefore , the system is linear.(ii) Consider an arbitrary inputs x 1(t).Let y 1(t)= t 2x 1(t-1)be the corresponding output .Consider a second input x 2(t) obtained by shifting x 1(t) in time:x 2(t)= x 1(t-t 0)The output corresponding to this input is y 2(t)= t 2x 2(t-1)= t 2x 1(t- 1- t 0)Also note that y 1(t-t 0)= (t-t 0)2x 1(t- 1- t 0)≠ y 2(t) Therefore the system is not time-invariant.(b) (i) Consider two arbitrary inputs x 1[n]and x 2[n]. x 1[n] → y 1[n] = x 12[n-2]x 2[n ] → y 2[n] = x 22[n-2].Let x 3(t) be a linear combination of x 1[n]and x 2[n].That is x 3[n]= ax 1[n]+b x 2[n]where a and b are arbitrary scalars. If x 3[n] is the input to the given system, then the corresponding output y 3[n] is y 3[n] = x 32[n-2]=(a x 1[n-2] +b x 2[n-2])2=a 2x 12[n-2]+b 2x 22[n-2]+2ab x 1[n-2] x 2[n-2]≠ay 1[n]+b y 2[n]Therefore the system is not linear.(ii) Consider an arbitrary input x 1[n]. Let y 1[n] = x 12[n-2]be the corresponding output .Consider a second input x 2[n] obtained by shifting x 1[n] in time:x 2[n]= x 1[n- n 0]The output corresponding to this input isy 2[n] = x 22[n-2].= x 12[n-2- n 0]Also note that y 1[n- n 0]= x 12[n-2- n 0] Therefore , y 2[n]= y 1[n- n 0] This implies that the system is time-invariant.(c) (i) Consider two arbitrary inputs x 1[n]and x 2[n].x 1[n] →y 1[n] = x 1[n+1]- x 1[n-1] x 2[n ]→y 2[n] = x 2[n+1 ]- x 2[n -1]Let x 3[n] be a linear combination of x 1[n] and x 2[n]. That is :x 3[n]= ax 1[n]+b x 2[n]where a and b are arbitrary scalars. If x 3[n] is the input to the given system, then the corresponding output y 3[n] is y 3[n]= x 3[n+1]- x 3[n-1]=a x 1[n+1]+b x 2[n +1]-a x 1[n-1]-b x 2[n -1]=a(x 1[n+1]- x 1[n-1])+b(x 2[n +1]- x 2[n -1])= ay 1[n]+b y 2[n]Therefore the system is linear.(ii) Consider an arbitrary input x 1[n].Let y 1[n]= x 1[n+1]- x 1[n-1]be the corresponding output .Consider a second input x 2[n] obtained by shifting x 1[n] in time: x 2[n]= x 1[n-n 0]The output corresponding to this input isy 2[n]= x 2[n +1]- x 2[n -1]= x 1[n+1- n 0]- x 1[n-1- n 0] Also note that y 1[n-n 0]= x 1[n+1- n 0]- x 1[n-1- n 0] Therefore , y 2[n]= y 1[n-n 0] This implies that the system is time-invariant.(d) (i) Consider two arbitrary inputs x 1(t) and x 2(t).x 1(t) → y 1(t)= d O {}(t) x 1 x 2(t) → y 2(t)= {}(t) x 2d OLet x 3(t) be a linear combination of x 1(t) and x 2(t).That is x 3(t)=a x 1(t)+b x 2(t)where a and b are arbitrary scalars. If x 3(t) is the input to the given system, then the corresponding output y 3(t) is y 3(t)= d O {}(t) x 3={}(t) x b +(t) ax 21d O=a d O {}(t) x 1+b {}(t) x 2d O = ay 1(t)+b y 2(t)Therefore the system is linear.(ii) Consider an arbitrary inputs x 1(t).Lety 1(t)= d O {}(t) x 1=2)(x -(t) x 11t -be the corresponding output .Consider a second input x 2(t) obtained by shifting x 1(t) in time:x 2(t)= x 1(t-t 0)The output corresponding to this input isy 2(t)= {}(t) x 2d O =2)(x -(t) x 22t -=2)(x -)t -(t x 0101t t --Also note that y 1(t-t 0)= 2)(x -)t -(t x 0101t t --≠ y 2(t)Therefore the system is not time-invariant.1.20 (a) Givenx )(t =jt e 2 y(t)=tj e 3x )(t =jte2- y(t)=tj e3-Since the system liner+=t j e t x 21(2/1)(jte 2-) )(1t y =1/2(tj e3+tj e3-)Thereforex1(t)=cos(2t))(1t y =cos(3t)(b) we know thatx 2(t)=cos(2(t-1/2))= (j e -jte 2+je jt e 2-)/2Using the linearity property, we may once again write x 1(t)=21( j e -jt e 2+je jt e 2-))(1t y=(je-jt e 3+je jt e 3-)= cos(3t-1)Therefore,x 1(t)=cos(2(t-1/2)))(1t y =cos(3t-1)1.21.The signals are sketched in figure S1.21.1.24 The even and odd parts are sketched in Figure S1.24 1.25 (a) periodic period=2π/(4)= π/2 (b) periodic period=2π/(4)= 2(c) x(t)=[1+cos(4t-2π/3)]/2. periodic period=2π/(4)= π/2 (d) x(t)=cos(4πt)/2. periodic period=2π/(4)= 1/2 (e) x(t)=[sin(4πt)u(t)-sin(4πt)u(-t)]/2. Not period. (f) Not period.1.26 (a) periodic, period=7.(b) Not period.(c) periodic, period=8.(d) x[n]=(1/2)[cos(3πn/4+cos(πn/4)). periodic, period=8. (e) periodic, period=16. 1.27 (a) Linear, stable(b) Not period. (c) Linear(d) Linear, causal, stable(e) Time invariant, linear, causal, stable (f) Linear, stable(g) Time invariant, linear, causal 1.28 (a) Linear, stable(b) Time invariant, linear, causal, stable (c)Memoryless, linear, causal (d) Linear, stable (e) Linear, stable(f) Memoryless, linear, causal, stable (g) Linear, stable1.29 (a) Consider two inputs to the system such that[][][]{}111.S e x n y n x n −−→=ℜand [][][]{}221.Se x n y n x n −−→=ℜNow consider a third inputx 3[n]= x2[n]+x 1[n]. The corresponding system outputWill be [][]{}[][]{}[]{}[]{}[][]33121212e e e e y n x n x n x n x n x n y n y n ==+=+=+ℜℜℜℜtherefore, we may conclude that the system is additive Let us now assume that inputs to the system such that [][][]{}/4111.Sj e x n y n e x n π−−→=ℜand[][][]{}/4222.Sj e x n y n e x n π−−→=ℜNow consider a third input x 3 [n]= x 2 [n]+ x 1 [n]. The corresponding system outputWill be[][]{}()[]{}()[]{}()[]{}()[]{}()[]{}()[]{}[]{}[]{}[][]/433331122/4/41212cos /4sin /4cos /4sin /4cos /4sin /4j e m e m e m e j j e e y n e x n n x n n x n n x n n x n n x n n x n e x n e x n y n y n πππππππππ==-+-+-=+=+ℜℜI ℜI ℜI ℜℜ therefore, we may conclude that the system is additive (b) (i) Consider two inputs to the system such that()()()()211111Sdx t x t y t x t dt ⎡⎤−−→=⎢⎥⎣⎦and ()()()()222211S dx t x t y t x t dt ⎡⎤−−→=⎢⎥⎣⎦ Now consider a third input x 3[t]= x2[t]+x 1[t]. The corresponding system outputWill be()()()()()()()()()2333211111211dx t y t x t dt d x t x t x t x t dt y t y t ⎡⎤=⎢⎥⎣⎦⎡⎤+⎡⎤⎣⎦=⎢⎥+⎢⎥⎣⎦≠+ therefore, we may conclude that the system is not additiveNow consider a third input x 4 [t]= a x 1 [t]. The corresponding system output Will be()()()()()()()()2444211211111dx t y t x t dt d ax t ax t dt dx t a x t dt ay t ⎡⎤=⎢⎥⎣⎦⎡⎤⎡⎤⎣⎦=⎢⎥⎢⎥⎣⎦⎡⎤=⎢⎥⎣⎦=Therefore, the system is homogeneous.(ii) This system is not additive. Consider the fowling example .Let δ[n]=2δ[n+2]+2δ[n+1]+2δ[n] andx2[n]=δ[n+1]+ 2δ[n+1]+ 3δ[n]. The corresponding outputs evaluated at n=0 are[][]120203/2y andy ==Now consider a third input x 3 [n]= x 2 [n]+ x 1 [n].= 3δ[n+2]+4δ[n+1]+5δ[n]The corresponding outputs evaluated at n=0 is y 3[0]=15/4. Gnarly, y 3[0]≠ ]0[][21y y n +.This[][][][][]444442,1010,x n x n x n y n x n otherwise ⎧--≠⎪=-⎨⎪⎩ [][][][][][]4445442,1010,x n x n ax n y n ay n x n otherwise ⎧--≠⎪==-⎨⎪⎩Therefore, the system is homogenous.1.30 (a) Invertible. Inverse system y(t)=x(t+4)(b)Non invertible. The signals x(t) and x 1(t)=x(t)+2πgive the same output (c) δ[n] and 2δ[n] give the same output d) Invertible. Inverse system; y(t)=dx(t)/dt(e) Invertible. Inverse system y(n)=x(n+1) for n ≥0 and y[n]=x[n] for n<0 (f) Non invertible. x (n) and –x(n) give the same result (g)Invertible. Inverse system y(n)=x(1-n) (h) Invertible. Inverse system y(t)=dx(t)/dt(i) Invertible. Inverse system y(n) = x(n)-(1/2)x[n-1] (j) Non invertible. If x(t) is any constant, then y(t)=0 (k) δ[n] and 2δ[n] result in y[n]=0 (l) Invertible. Inverse system: y(t)=x(t/2)(m) Non invertible x 1 [n]= δ[n]+ δ[n-1]and x 2 [n]= δ[n] give y[n]= δ[n] (n) Invertible. Inverse system: y[n]=x[2n]1.31 (a) Note that x 2[t]= x 1 [t]- x 1 [t-2]. Therefore, using linearity we get y 2 (t)= y 1 (t)- y 1 (t-2).this is shown in Figure S1.31(b)Note that x3 (t)= x1 [t]+ x1 [t+1]. .Therefore, using linearity we get Y3 (t)= y1 (t)+ y1 (t+2). this is2(4) y 2(t) periodic, period T; x(t) periodic, period T/2;1.33(1) True x[n]=x[n+N ]; y 1 (n)= y 1 (n+ N 0)i.e. periodic with N 0=n/2if N is even and with period N 0=n if N is odd.(2)False. y 1 [n] periodic does no imply x[n] is periodic i.e. Let x[n] = g[n]+h[n] where0,1,[][]0,(1/2),nn even n even g n and h n n odd n odd⎧⎧==⎨⎨⎩⎩ Then y 1 [n] = x [2n] is periodic but x[n] is clearly not periodic. (3)True. x [n+N] =x[n]; y 2 [n+N 0] =y 2 [n] where N 0=2N (4) True. y 2 [n+N] =y 2 [n]; y 2 [n+N 0 ]=y 2 [n] where N 0=N/2 1.34. (a) ConsiderIf x[n] is odd, x[n] +x [-n] =0. Therefore, the given summation evaluates to zero. (b) Let y[n] =x 1[n]x 2[n] .Theny [-n] =x 1[-n] x 2[-n] =-x 1[n]x 2[n] =-y[n]. This implies that y[n] is odd.(c)ConsiderUsing the result of part (b), we know that x e [n]x o [n] is an odd signal .Therefore, using the result of part (a) we may conclude thatTherefore,(d)ConsiderAgain, since x e (t) x o (t) is odd,Therefore,1.35. We want to find the smallest N 0 such that m(2π /N) N 0 =2πk or N 0 =kN/m,{}1[][0][][]n n x n x x n x n ∞∞=-∞==++-∑∑22[][]e o n n n n x x ∞∞=-∞=-∞=+∑∑222[][][]e on n n n n n x x x∞∞∞=-∞=-∞=-∞==+∑∑∑2[][]0eon n n x x ∞=-∞=∑222[][][].e on n n n n n xx x ∞∞∞=-∞=-∞=-∞==+∑∑∑2220()()()2()().eoet dt t dt t dt t t dt x x x x x ∞∞∞∞-∞-∞-∞-∞=++⎰⎰⎰⎰0()()0.et t dt x x ∞-∞=⎰222()()().e ot dt t dt t dt xx x ∞∞∞-∞-∞-∞=+⎰⎰⎰()()()()()().xy yx t x t y d y t x d t φττττττφ∞-∞∞-∞=+=-+=-⎰⎰where k is an integer, then N must be a multiple of m/k and m/k must be an integer .this implies that m/k is a divisor of both m and N .Also, if we want the smallest possible N 0, then m/k should be the GCD of m and N. Therefore, N 0=N/gcd(m,N).1.36．(a)If x[n] is periodic 0(),0..2/j n N T o ewhere T ωωπ+= This implies that 022o T kNT k T T Nππ=⇒==a rational number . (b)T/T 0 =p/q then x[n] =2(/)j n p q e π,The fundamental period is q/gcd(p,q) and the fundmental frequencyis(c) p/gcd(p,q) periods of x(t) are needed .1.37.(a) From the definition of ().xy t φWe havepart(a) that()().xx xx t t φφ=-This implies that ()xy t φis(b) Note from even .Therefore,the odd part of ().xx t φis zero.(c) Here, ()().xy xx t t T φφ=-and ()().yy xx t t φφ= 1.38.(a) We know that /22(2)().t t δδ=ThereforeThis implies that1(2)().2t t δδ=(b)The plot are as shown in Figure s3.18. 1.39 We havelim ()()lim (0)()0.u t t u t δδ→→==Also,0022gcd(,)gcd(,)gcd(,)gcd(,).T pp q p q p q p q q p q p pωωππ===/21lim (2)lim ().2t t δδ→∞→∞=01lim ()()().2u t t t δδ→=u Δ'（t ） 1 1/2Δ/2-Δ/2t 0tu Δ'（t ）12Δ t 0tu Δ'（t ） 1 1/2Δ-Δttu Δ'（t ）1 1/2Δ-Δt 0t⎰⎰∞∞∞--=-=0)()()()()(ττδτττδτd t u d t u t gTherefore,0,0()1,00t g t t undefined for t >⎧⎪=<⎨⎪=⎩()0()()()t u t t δττδτδτ-=-=-1.40.(a) If a system is additive ,then also, if a system is homogeneous,then(b) y(t)=x 2(t) is such a systerm . (c) No.For example,consider y(t) ()()ty t x d ττ-∞=⎰with ()()(1).x t u t u t =--Then x(t)=0for t>1,but y(t)=1 for t>1.1.41. (a) y[n]=2x[n].Therefore, the system is time invariant.(b) y[n]=(2n-1)x[n].This is not time-invariant because y[n- N 0]≠(2n-1)2x [n- N 0]. (c) y[n]=x[n]{1+(-1)n +1+(-1)n-1}=2x[n].Therefore, the system is time invariant .1.42.(a) Consider two system S 1 and S 2 connected in series .Assume that if x 1(t) and x 2(t) arethe inputs to S 1..then y 1(t) and y 2(t) are the outputs.respectively .Also,assume thatif y 1(t) and y 2(t) are the input to S 2 ,then z 1(t) and z 2(t) are the outputs, respectively . Since S 1 is linear ,we may write()()()()11212,s ax t bx t ay t by t +→+where a and b are constants. Since S 2 is also linear ,we may write()()()()21212,s ay t by t az t bz t +→+We may therefore conclude that)()()()(212121t b t a t b t a z z x x s s +−→−+Therefore ,the series combination of S 1 and S 2 is linear. Since S 1 is time invariant, we may write()()11010s x t T y t T -→-and()()21010s y t T z t T -→-Therefore,()()121010s s x t T z t T -→-Therefore, the series combination of S 1 and S 2 is time invariant.(b) False, Let y(t)=x(t)+1 and z(t)=y(t)-1.These corresponds to two nonlinear systems. If these systems are connected in series ,then z(t)=x(t) which is a linear system.00.()().00x t y t =→=0()()()()0x t x t y t y t =-→-=(c) Let us name the output of system 1 as w[n] and the output of system 2 as z[n] .Then11[][2][2][21][22]24y n z n w n w n w n ==+-+-[][][]241121-+-+=n x n x n xThe overall system is linear and time-invariant.1.43. (a) We have())(t y t x s−→−Since S is time-invariant.())(T t y T t x s-−→−-Now if x (t) is periodic with period T. x{t}=x(t-T). Therefore, we may conclude that y(t)=y(t-T).This impliesthat y(t) is also periodic with T .A similar argument may be made in discrete time . (b)1.44 (a) Assumption : If x(t)=0 for t<t 0 ,then y(t)=0 for t< t 0.To prove That : The system is causal.Let us consider an arbitrary signal x 1(t) .Let us consider another signal x 2(t) which is the same as x 1(t)fort< t 0. But for t> t 0 , x 2(t) ≠x 1(t),Since the system is linear,()()()()1212,x t x t y t y t -→-Since ()()120x t x t -=for t< t 0 ,by our assumption =()()120y t y t -=for t< t 0 .This implies that()()12y t y t =for t< t 0 . In other words, t he output is not affected by input values for 0t t ≥. Therefore, thesystem is causal .Assumption: the system is causal . To prove that :If x(t)=0 for t< t 0 .then y(t)=0 for t< t 0 .Let us assume that the signal x(t)=0 for t< t 0 .Then we may express x(t) as ()()12()x t x t x t =-, Where()()12x t x t = for t< t 0 . the system is linear .the output to x(t) will be()()12()y t y t y t =-.Now ,since the system is causal . ()()12y t y t = for t< t 0 .implies that()()12y t y t = for t< t 0 .Therefore y(t)=0 for t< t 0 .(b) Consider y(t)=x(t)x(t+1) .Now , x(t)=0 for t< t 0 implies that y(t)=0 for t< t 0 .Note that the system is nonlinear and non-causal .(c) Consider y(t)=x(t)+1. the system is nonlinear and causal .This does not satisfy the condition of part(a). (d) Assumption: the system is invertible. To prove that :y[n]=0 for all n only if x[n]=0 for all n . Consider[]0[]x n y n =→. Since the system is linear :2[]02[]x n y n =→.Since the input has not changed in the two above equations ,we require that y[n]= 2y[n].This implies that y[n]=0. Since we have assumed that the system is invertible , only one input could have led to this particular output .That input must be x[n]=0 .Assumption: y[n]=0 for all n if x[n]=0 for all n . To prove that : The system is invertible . Suppose that11[][]x n y n → and21[][]x n y n →Since the system is linear ,1212[][][][]0x n x n y n y n -=→-=By the original assumption ,we must conclude that 12[][]x n x n =.That is ,any particular y 1[n] can be produced that by only one distinct input x 1[n] .Therefore , the system is invertible. (e) y[n]=x 2[n]. 1.45. (a) Consider ,()111()()shx x t y t t φ→= and()222()()shx x t y t t φ→=.Now, consider ()()()312x t ax t bx t =+. The corresponding system output will be()()12331212()()()()()()()()()hx hx y t x h t d a x h t d b x t h t d a t b t ay t by t ττττττττφφ∞-∞∞∞-∞-∞=+=+++=+=+⎰⎰⎰Therefore, S is linear .Now ,consider x 4(t)=x 1(t-T).The corresponding system output will be()14411()()()()()()()hx y t x h t d x T h t d x h t T d t T τττττττττφ∞-∞∞-∞∞-∞=+=-+=++=+⎰⎰⎰Clearly, y 4(t)≠ y 1(t-T).Therefore ,the system is not time-invariant.The system is definitely not causal because the output at any time depends on future values of the input signal x(t).(b) The system will then be linear ,time invariant and non-causal. 1.46. The plots are in Figure S1.46.1.47.(a) The overall response of the system of Figure P1.47.(a)=(the response of the system to x[n]+x 1[n])-the response of the system to x 1[n]=(Response of a linear system L to x[n]+x 1[n]+zero input response of S)- (Response of a linear system L to x 1[n]+zero input response of S)=( (Response of a linear system L to x[n]).。
离散时间信号处理奥本海姆第二版课后答案第八章
第八章 离散傅立叶变换8.1 假设()t x c 是一个周期的连续时间信号，其周期为1ms ，它的傅立叶级数为()()∑-=-=9910/23k kt j kc e a t x π. 对于9>k ，傅立叶系数k a 为零，以采样间隔s T 31061-⨯=对()t x c 采样得到[]n x ： []⎪⎪⎭⎫⎝⎛=-6103n x n x c .(a) []n x 是周期的吗？如果是，周期为多少？(b) 采样率是否高于奈奎斯特采样率，也就是说T 是否充分小而且可以避免混叠？ (c) 利用k a 求出[]n x 的离散傅立叶级数系数。
解：（a ）[]∑∑-=-=⎪⎪⎭⎫ ⎝⎛⨯-==⎪⎪⎭⎫ ⎝⎛=--996299610102333610k kn jkk n k j k c ea e a n x n x ππ而() 1,0,62662==+l ee kn jl n k jππ[][]l n x n x 6+=∴∴ []n x 是周期的，周期为6。
（b ）30102-=Ωπ而采样频率为03321012106122Ω>=⨯==Ω--πππT 所以T 足够小，而可以避免混叠。
（c ）[][]()()()∑∑∑∑∑∑-=---==-=--=-=--=⎪⎪⎭⎫ ⎝⎛=⎪⎪⎭⎫ ⎝⎛==99335995062506299621011k k l k l lk n k l n j l n kn j l nl j l N n knNeea e a e e a w n x k X πππππ 8.2 设[]n x ~是一个周期为N 的周期序列，[]n x ~还是一个周期为3N 的周期序列。
令[]k X ~表示作为周期为N 的周期序列的[]n x ~的DFS 系数，[]k X ~3表示作为周期为3N 的周期序列的[]n x ~的DFS 系数。
(a) 用[]k X ~表示出[]k X ~3。
(b) 用公式计算[]k X ~和[]k X ~3，当[]n x ~为图P8.2中给定的序列时，证明你在(a)中得出的结果。
信号与系统 奥本海姆 中文答案 chapter 8
Chapter 88.6解：x （t ）的傅里叶变换()m ,0j X ωωω>=故x （t ）的频谱图为()()()()[]()[]()[]{}C C C C c j x j x 21j X 21t cos t x ωωωωωωδωωδπωπω++-=++-*↔其频谱图为ttsin C πω的频谱图为故()()()⎥⎦⎤⎢⎣⎡⎪⎭⎫⎝⎛*=t t sin t cos t x -t cos t x t g c c c πωωω的频谱图为故()t cos t g c ω的频谱图为()()()ttAsin t cos t g t x c πωω*=4A =8.9解：(a) 因为1()x t 和2()x t 的截止频率都为c ω，1()x t 经频率为c ω的载波信号调制器经AM —SSB/SC 技术保留下边带后截止频率为c ω。
2()x t 经频率为2c ω的载波信号调制器经AM —SSB/SC 技术保留下边带后有2c c ωωω<<时不为0，其它都为0。
所以，将二者加在一起截止频率为2c ω。
即：2c ωω>时，()0Y j ω=。
(b) 2A =8.12解：2000M ωπ=2c M ωω∴>，即：32220000.510T Tππ->⨯⇒<⨯又410.51010T -∆=⇒∆<⨯8.13解：(a) 11212111()()(1cos)2222j t T j t T T p t P j e d e d πωωπωωωωππ++∞-∞-==+⎰⎰112121111111422sin 1(0)(1cos)()22242T T T p d T T T T ππωππωππ+-∴=+=+=⎰(b) 因为在PAM 中，在1t kT =采样后，来自其它所有脉冲对这个采样值贡献为零，即1()0p t mT -=，m k ≠。
所以，当(0)0p =时，1()0p kT =（1,2,k =±± ）8.16解：{}00()(2)(2)j l C e l l jωπδωωπδωωπ+∞=-∞=---+-∑1()()()2j j j Y e X e C e ωωωπ=* 1()()(2)(2)222j j l Y e X e l l j ωωπππδωπδωππ+∞=-∞⎧⎫∴=*---+-⎨⎬⎩⎭∑ 因而在0ωπ≤≤内， 当308ωπ≤≤或38πωπ≤≤时，()0j Y e ω=。
信号与系统奥本海姆英文版课后答案chapter8
X ( j (ω + ωc ))
Y ( jω )
X ( j (ω − ωc ))
−ω c
0
ωc
−ωc +1000π
Figure S8.2
If
ωc − 1000π
we want to prevent the two shifted replicas of
from multiplied by cos(2000π t ) , the output will be 1 x1 (t ) = g (t ) cos(2000π t ) = x (t ) sin(2000π t ) cos(2000π t ) = x(t ) sin(4000π t ) 2 The Fourier transform of this signal is 1 1 X 1 ( jw) = X ( j (ω − 4000π )) − X ( j (ω + 4000π )) .
x(t ) from g (t ) cos(ωc t ) ,then we have to pass g (t ) cos(ωc t ) through an ideal lowpass filter with gain
ωM .Therefore ,A=4. 8.7 In Figure S8.7 ,we show X ( jω ) , G ( jω ) ,and Q ( jω ) .We also show a polt of The Fourier transform of g (t ) cos(ωc t ) ,then we need to ensure that (1) ω0 = 2ωc , and (2) an ideal lowpass filter with passband gain of 2 and a cutoff frequency of ωc is used to filter g (t ) cos(ω0t ) .
信号与系统课后习题答案第8章
7
第8章 系统的状态空间分析
题图 8.2
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第8章 系统的状态空间分析
9
第8章 系统的状态空间分析
题解图 8.2
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第8章 系统的状态空间分析
(2)
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第8章 系统的状态空间分析
8.3 作为练习，请用MATLAB软件绘制x1(t)、x2(t)波形图 和x(t)的状态轨迹。
8.4 同题8.3。
代入元件值，整理得状态方程:
观察网络，直接写出输出方程:
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第8章 系统的状态空间分析
题解图 8.10
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
8.11 列出题图 8.9 网络的状态空间方程(以uC、iL为状态变 量；i0、u0为输出)。
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第8章 系统的状态空间分析
题解图 8.29
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第8章 系统的状态空间分析
在系统输出端写出输出方程:
整理成矩阵形式，有
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
8.31 已知离散时间系统的模拟框图如题图 8.14 所示,试建 立其状态空间方程，并求出输入为
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第8章 系统的状态空间分析
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第8章 系统的状态空间分析
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信号与系统课后答案8
故得零状态响应为
1 3 y f (k ) = [2(2)k + (−1) k − (1) k ]U (k ) 2 2
故又得全响应为
1 3 y (k ) = yx (k ) + y f (k ) = [2(2) k − (−1) k ]U (k + 2) + [2(2)k + (−1)k − (1)k ]U (k ) 2 2
第八章 习 题
8.1 求长度为 N 的斜坡序列
k , RN (k ) = 0,
0 ≤ k ≤ N −1 k < 0, k ≥ N
的 z 变换 RN ( z ) ，并求 N = 4 时的 RN ( z ) (见图题 81)。
R N (k )
L
答案
解 方法一
设GN (k ) = U (k ) − U (k − N ), 则 RN (k ) = kGN (k )
答案
解
(1)
F ( z ) = z1 [
z +1 1 3 1 3 ( z − 1)( z − − j )( z − + j ) 2 2 2 2 2z z z = −[ + ] π π j −j z −1 z−e 3 z−e 3
] = z[
2 + z −1
−1 1 3 z− − j 2 2
+
−1 1 3 z− + j 2 2
∞
z <
1 2
（3） F ( z ) =
z z− 1 4
−
z z− 2 3
=
−5 z , 1 2 12( z − )( z − ) 4 3
z >
2 3
1 2 极点P , P2 = ; 零点z1 = 0。 1 = 4 3
信号与系统奥本海姆习题答案
Chapter 1 Answers1.6 (a).NoBecause when t<0, )(1t x =0.(b).NoBecause only if n=0, ][2n x has valuable.(c).Yes Because ∑∞-∞=--+--+=+k k m n k m n m n x ]}414[]44[{]4[δδ ∑∞-∞=------=k m k n m k n )]}(41[)](4[{δδ ∑∞-∞=----=k k n k n ]}41[]4[{δδ N=4.1.9 (a). T=π/5Because 0w =10, T=2π/10=π/5.(b). Not periodic.Because jt t e e t x --=)(2, while t e -is not periodic, )(2t x is not periodic.(c). N=2Because 0w =7π, N=(2π/0w )*m, and m=7.(d). N=10Because n j j e e n x )5/3(10/343)(ππ=, that is 0w =3π/5, N=(2π/0w )*m, and m=3.(e). Not periodic. Because 0w =3/5, N=(2π/0w )*m=10πm/3 , it ’s not a rational number.1.14 A1=3, t1=0, A2=-3, t2=1 or -1dtt dx )( isSolution: x(t) isBecause ∑∞-∞=-=k k t t g )2()(δ, dt t dx )(=3g(t)-3g(t-1) or dtt dx )(=3g(t)-3g(t+1) 1.15. (a). y[n]=2x[n-2]+5x[n-3]+2x[n-4]Solution:]3[21]2[][222-+-=n x n x n y ]3[21]2[11-+-=n y n y ]}4[4]3[2{21]}3[4]2[2{1111-+-+-+-=n x n x n x n x ]4[2]3[5]2[2111-+-+-=n x n x n xThen, ]4[2]3[5]2[2][-+-+-=n x n x n x n y(b).No. For it ’s linearity.the relationship between ][1n y and ][2n x is the same in-out relationship with (a). you can have a try.1.16. (a). No.For example, when n=0, y[0]=x[0]x[-2]. So the system is memory. (b). y[n]=0.When the input is ][n A δ,then, ]2[][][2-=n n A n y δδ, so y[n]=0. (c). No.For example, when x[n]=0, y[n]=0; when x[n]=][n A δ, y[n]=0. So the system is not invertible.1.17. (a). No.For example, )0()(x y =-π. So it ’s not causal.(b). Yes.Because : ))(sin()(11t x t y = , ))(sin()(22t x t y =))(sin())(sin()()(2121t bx t ax t by t ay +=+1.21. Solution:We have known:(a).(b).(c).(d).1.22. Solution:We have known:(a).(b).(e).(g)1.23. Solution:For )]()([21)}({t x t x t x E v -+= )]()([21)}({t x t x t x O d --= then,(a).(b).(c).1.24.For: ])[][(21]}[{n x n x n x E v -+= ])[][(21]}[{n x n x n x O d --=then,(a).(b).1.25. (a). Periodic. T=π/2.Solution: T=2π/4=π/2.(b). Periodic. T=2.Solution: T=2π/π=2.(d). Periodic. T=0.5. Solution: )}()4{cos()(t u t E t x v π=)}())(4cos()()4{cos(21t u t t u t --+=ππ )}()(){4cos(21t u t u t -+=π )4cos(21t π= So, T=2π/4π=0.51.26. (a). Periodic. N=7Solution: N=m *7/62ππ=7, m=3.(b). Aperriodic.Solution: N=ππm m 16*8/12=, it ’s not rational number.(e). Periodic. N=16 Solution as follow:)62cos(2)8sin()4cos(2][ππππ+-+=n n n n x in this equation,)4cos(2n π, it ’s period is N=2π*m/(π/4)=8, m=1.)8sin(n π, it ’s period is N=2π*m/(π/8)=16, m=1.)62cos(2ππ+-n , it ’s period is N=2π*m/(π/2)=4, m=1. So, the fundamental period of ][n x is N=(8,16,4)=16.1.31. SolutionBecause )()1()(),2()()(113112t x t x t x t x t x t x ++=--=. According to LTI property ,)()1()(),2()()(113112t y t y t y t y t y t y ++=--=Extra problems:Sketch ⎰∞-=t dt t x t y )()(. 1. SupposeSolution:2. SupposeSketch:(1). )]1(2)1()3()[(--+++t t t t g δδδ(2). ∑∞-∞=-k k t t g )2()(δ(2).Chapter 22.1 Solution:Because x[n]=(1 2 0 –1)0, h[n]=(2 0 2)1-, then(a).So, ]4[2]2[2]1[2][4]1[2][1---+-+++=n n n n n n y δδδδδ (b). according to the property of convolutioin:]2[][12+=n y n y(c). ]2[][13+=n y n y][*][][n h n x n y =][][k n h k x k -=∑∞-∞= ∑∞-∞=-+--=k k k n u k u ]2[]2[)21(2 ][211)21()21(][)21(12)2(0222n u n u n n k k --==+-++=-∑ ][])21(1[21n u n +-= the figure of the y[n] is:2.5 Solution:We have known: ⎩⎨⎧≤≤=elsewhere n n x ....090....1][，，, ⎩⎨⎧≤≤=elsewhere N n n h ....00....1][，，,(9≤N ) Then, ]10[][][--=n u n u n x , ]1[][][---=N n u n u n h∑∞-∞=-==k k n u k h n h n x n y ][][][*][][ ∑∞-∞=-------=k k n u k n u N k u k u ])10[][])(1[][(So, y[4] ∑∞-∞=-------=k k u k u N k u k u ])6[]4[])(1[][( ⎪⎪⎩⎪⎪⎨⎧≥≤=∑∑==4,...14, (140)0N N k Nk =5, then 4≥N And y[14] ∑∞-∞=------=k k u k u N k u k u ])4[]14[])(1[][(⎪⎪⎩⎪⎪⎨⎧≥≤=∑∑==14,...114, (1145)5N N k Nk =0, then 5<N ∴4=N2.7 Solution:[][][2]k y n x k g n k ∞=-∞=-∑（a ）[][1]x n n δ=-,[][][2][1][2][2]k k y n x k g n k k g n k g n δ∞∞=-∞=-∞=-=--=-∑∑(b) [][2]x n n δ=-,[][][2][2][2][4]k k y n x k g n k k g n k g n δ∞∞=-∞=-∞=-=--=-∑∑ (c) S is not LTI system..(d) [][]x n u n =,0[][][2][][2][2]k k k y n x k g n k u k g n k g n k ∞∞∞=-∞=-∞==-=-=-∑∑∑2.8 Solution: )]1(2)2([*)()(*)()(+++==t t t x t h t x t y δδ )1(2)2(+++=t x t xThen,That is, ⎪⎪⎪⎩⎪⎪⎪⎨⎧≤<-≤<-+-=-<<-+=others t t t t t t t t y ,........010,....2201,.....41..,.........412,.....3)(2.10 Solution:(a). We know:Then,)()()(αδδ--='t t t h)]()([*)()(*)()(αδδ--='='t t t x t h t x t y )()(α--=t x t xthat is,So, ⎪⎪⎩⎪⎪⎨⎧+≤≤-+≤≤≤≤=others t t t t t t y ,.....011,.....11,....0,.....)(ααααα(b). From the figure of )(t y ', only if 1=α, )(t y ' would contain merely therediscontinuities.2.11 Solution:(a). )(*)]5()3([)(*)()(3t u et u t u t h t x t y t----==⎰⎰∞∞---∞∞--------=ττττττττd t u e u d t u eu t t )()5()()3()(3)(3⎰⎰-------=tt t t d e t u d et u 5)(33)(3)5()3(ττττ⎪⎪⎪⎪⎩⎪⎪⎪⎪⎨⎧≥+-=-<≤-=<=---------⎰⎰⎰5,.......353,.....313.........,.........0315395)(33)(3393)(3t e e d e d e t e d e t tt t t t t t t t ττττττ(b). )(*)]5()3([)(*)/)(()(3t u e t t t h dt t dx t g t ----==δδ)5()3()5(3)3(3---=----t u e t u e t t(c). It ’s obvious that dt t dy t g /)()(=.2.12 Solution∑∑∞-∞=-∞-∞=--=-=k tk tk t t u ek t t u e t y )]3(*)([)3(*)()(δδ∑∞-∞=---=k k t k t u e)3()3(Considering for 30<≤t ,we can obtain33311])3([)(---∞=-∞-∞=--==-=∑∑ee e ek t u e e t y tk k tk kt. (Because k must be negetive ,1)3(=-k t u for 30<≤t ).2.19 Solution:(a). We have known:][]1[21][n x n w n w +-=(1) ][]1[][n w n y n y βα+-=(2)from (1), 21)(1-=E EE Hfrom (2), αβ-=E EE H )(2then, 212212)21(1)21)(()()()(--++-=--==E E E E E E H E H E H ααβαβ∴][]2[2]1[)21(][n x n y n y n y βαα=-+-+-but, ][]1[43]2[81][n x n y n y n y +-+--=∴⎪⎩⎪⎨⎧=⎪⎭⎫ ⎝⎛=+=143)21(:....812βααor ∴⎪⎩⎪⎨⎧==141βα(b). from (a), we know )21)(41()()()(221--==E E E E H E H E H21241-+--=E EE E ∴][)41()21(2][n u n h n n ⎥⎦⎤⎢⎣⎡-=2.20 (a). 1⎰⎰∞∞-∞∞-===1)0cos()cos()()cos()(0dt t t dt t t u δ(b). 0dt t t )3()2sin(5+⎰δπ has value only on 3-=t , but ]5,0[3∉-∴dt t t )3()2sin(5+⎰δπ=0(c). 0⎰⎰---=-641551)2cos()()2cos()1(dt t t u d u πτπττ⎰-'-=64)2cos()(dt t t πδ0|)2(s co ='=t t π 0|)2sin(20=-==t t ππ∑∞-∞=-==k t h kT t t h t x t y )(*)()(*)()(δ∑∞-∞=-=k kT t h )(∴2.27Solution()y A y t dt ∞-∞=⎰,()xA x t dt ∞-∞=⎰,()hA h t dt ∞-∞=⎰.()()*()()()y t x t h t x x t d τττ∞-∞==-⎰()()()()()()()()()(){()}y x hA y t dt x x t d dtx x t dtd x x t dtd x x d d x d x d A A ττττττττττξξτττξξ∞∞∞-∞-∞-∞∞∞∞∞-∞-∞-∞-∞∞∞∞∞-∞-∞-∞-∞==-=-=-===⎰⎰⎰⎰⎰⎰⎰⎰⎰⎰⎰(a) ()()(2)tt y t e x d τττ---∞=-⎰,Let ()()x t t δ=,then ()()y t h t =. So , 2()(2)(2)()(2)()(2)t t t t t h t ed e d e u t τξδττδξξ---------∞-∞=-==-⎰⎰(b) (2)()()*()[(1)(2)]*(2)t y t x t h t u t u t e u t --==+---(2)(2)(1)(2)(2)(2)t t u eu t d u e u t d ττττττττ∞∞-------∞-∞=+------⎰⎰22(2)(2)12(1)(4)t t t t u t e d u t e d ττττ---------=---⎰⎰(2)2(2)212(1)[]|(4)[]|t t t t u t e e u t ee ττ-------=--- (1)(4)[1](1)[1](4)t t e u t e u t ----=-----2.46 SolutionBecause)]1([2)1(]2[)(33-+-=--t u dtde t u e dt d t x dt d t t )1(2)(3)1(2)(333-+-=-+-=--t e t x t e t x t δδ.From LTI property ,we know)1(2)(3)(3-+-→-t h e t y t x dtdwhere )(t h is the impulse response of the system. So ,following equation can be derived.)()1(223t u e t h e t --=-Finally, )1(21)()1(23+=+-t u e e t h t 2.47 SoliutionAccording to the property of the linear time-invariant system: (a). )(2)(*)(2)(*)()(000t y t h t x t h t x t y ===(b). )(*)]2()([)(*)()(00t h t x t x t h t x t y --==)(*)2()(*)(0000t h t x t h t x --=012y(t)t4)2()(00--=t y t y(c). )1()1(*)(*)2()1(*)2()(*)()(00000-=+-=+-==t y t t h t x t h t x t h t x t y δ(d). The condition is not enough.(e). )(*)()(*)()(00t h t x t h t x t y --==τττd t h x )()(00+--=⎰∞∞-)()()(000t y dm m t h m x -=--=⎰∞∞-(f). )()]([)](*)([)(*)()(*)()(000000t y t y t h t x t h t x t h t x t y "=''='--'=-'-'==Extra problems:1. Solute h(t), h[n](1). )()(6)(5)(22t x t y t y dt dt y dtd =++ (2). ]1[][2]1[2]2[+=++++n x n y n y n y Solution:(1). Because 3121)3)(2(1651)(2+-++=++=++=P P P P P P P Hso )()()()3121()(32t u e e t P P t h t t ---=+-++=δ (2). Because )1)(1(1)1(22)(22i E i E EE E E E E E H -+++=++=++=iE Eii E E i -+-+++=1212 so []][)1()1(2][1212][n u i i i k i E E i i E E i n h n n +----=⎪⎪⎪⎪⎭⎫⎝⎛-+-+++=δChapter 33.1 Solution:Fundamental period 8T =.02/8/4ωππ==00000000033113333()224434cos()8sin()44j kt j t j t j t j tk k j t j t j t j tx t a e a e a e a e a e e e je je t t ωωωωωωωωωππ∞----=-∞--==+++=++-=-∑3.2 Solution:for, 10=a , 4/2πj ea --= , 4/2πj ea = , 3/42πj ea --=, 3/42πj ea =n N jk k N k e a n x )/2(][π∑>=<=n j n j n j n j e a e a e a e a a )5/8(4)5/8(4)5/4(2)5/4(20ππππ----++++=n j j n j j n j j n j j e e e e e e e e )5/8(3/)5/8(3/)5/4(4/)5/4(4/221ππππππππ----++++= )358cos(4)454cos(21ππππ++++=n n)6558sin(4)4354sin(21ππππ++++=n n3.3 Solution: for the period of )32cos(t πis 3=T , the period of )35sin(t πis 6=Tso the period of )(t x is 6 , i.e. 3/6/20ππ==w)35sin(4)32cos(2)(t t t x ππ++= )5sin(4)2cos(21200t w t w ++=)(2)(21200005522t w j t w j t w j t w j e e j e e ----++=then, 20=a , 2122==-a a , j a 25=-, j a 25-=3.5 Solution:(1). Because )1()1()(112-+-=t x t x t x , then )(2t x has the same period as )(1t x ,that is 21T T T ==, 12w w =(2). 212111()((1)(1))jkw t jkw tk T T b x t e dt x t x t e dt T--==-+-⎰⎰111111(1)(1)jkw tjkw t T Tx t e dt x t e dt T T --=-+-⎰⎰ 111)(jkw k k jkw k jkw k e a a e a e a -----+=+=3.8 Solution:kt jw k k e a t x 0)(∑∞-∞==while:)(t x is real and odd, then 00=a , k k a a --=2=T , then ππ==2/20wand0=k a for 1>kso kt jw k k e a t x 0)(∑∞-∞==t jw t jw e a e a a 00110++=--)sin(2)(11t a e e a t j t j πππ=-=-for12)(2121212120220==++=-⎰a a a a dt t x∴2/21±=a ∴)sin(2)(t t x π±=3.13 Solution:Fundamental period 8T =.02/8/4ωππ==kt jw k k e a t x 0)(∑∞-∞==∴t jkw k k e jkw H a t y 0)()(0∑∞-∞==0004, 0sin(4)()0, 0k k H jk k k ωωω=⎧==⎨≠⎩ ∴000()()4jkw t k k y t a H jkw e a ∞=-∞==∑Because 48004111()1(1)088T a x t dt dt dt T ==+-=⎰⎰⎰So ()0y t =.kt jw k k e a t x 0)(∑∞-∞==∴t jkw k k e jkw H a t y 0)()(0∑∞-∞== ∴dt e jkw H t y Ta t jkw Tk 0)()(10-⎰=for⎪⎩⎪⎨⎧>≤=100, (0100),.......1)(w w jw H ∴if 0=k a , it needs 1000>kwthat is 12100,........1006/2>>k kππand k is integer, so 8>K3.22 Solution:021)(1110===⎰⎰-tdt dt t x Ta Tdt te dt te dt e t x T a t jk t jk t jkw T k ππ-----⎰⎰⎰===1122112121)(10t jk tde jk ππ--⎰-=1121⎥⎥⎦⎤⎢⎢⎣⎡---=----111121ππππjk e te jk t jk tjk ⎥⎦⎤⎢⎣⎡---+-=--ππππππjk e e e e jk jk jk jk jk )()(21⎥⎦⎤⎢⎣⎡-+-=ππππjk k k jk )sin(2)cos(221[]πππππk jk k j k jk k)1()cos()cos(221-==-=0............≠k404402()()1184416tj tj t t j tt j t H j h t edt ee dte edt e e dtj j ωωωωωωωω∞∞----∞-∞∞----∞===+=+=-++⎰⎰⎰⎰A periodic continous-signal has Fourier Series:. 0()j kt k k x t a e ω∞=-∞=∑T is the fundamental period of ()x t .02/T ωπ=The output of LTI system with inputed ()x t is 00()()jk t k k y t a H jk e ωω∞=-∞=∑Its coefficients of Fourier Series: 0()k k b a H jk ω= (a)()()n x t t n δ∞=-∞=-∑.T=1, 02ωπ=11k a T==. 01/221/21()()1jkw t jk tk T a x t e dt t e dt Tπδ---===⎰⎰ （Note ：If ()()n x t t nT δ∞=-∞=-∑,1k a T=） So 2282(2)16(2)4()k k b a H jk k k πππ===++ (b)()(1)()n n x t t n δ∞=-∞=--∑ .T=2, 0ωπ=,11k a T== 01/23/21/21/2111()()(1)(1)221[1(1)]2jkw t jk tjk t k T k a x t e dt t e dt t e dtT ππδδ----==+--=--⎰⎰⎰So 24[1(1)]()16()k k k b a H jk k ππ--==+, (c) T=1,02ωπ=01/421/4sin()12()jk t jk tk T k a x t e dt e dt Tk ωπππ---===⎰⎰28sin()2()[16(2)]k k k b a H jk k k ππππ==+ 3.35 Solution: T= /7π,02/14T ωπ==.kt jw k k e a t x 0)(∑∞-∞==∴t jkw k k e jkw H a t y 0)()(0∑∞-∞==∴0()k k b a H jkw =for⎩⎨⎧≥=otherwise w jw H ,.......0250,.......1)(,01,. (17)()0,.......k H jkw otherwise ⎧≥⎪=⎨⎪⎩that is 0250250, (14)k k ω<<, and k is integer, so 18....17k or k <≤. Let ()()y t x t =,k k b a =, it needs 0=k a ,for 18....17k or k <≤.3.37 Solution:11()[]()212()21312411511cos 224nj j nj n n n n j nn j nn n j j j H e h n ee ee e e e ωωωωωωωωω∞∞--=-∞=-∞-∞--=-∞=-===+=+=---∑∑∑∑A periodic sequence has Fourier Series:2()[]jk n Nk k N x n a eπ=<>=∑.N is the fundamental period of []x n .The output of LTI system with inputed []x n is 22()[]()jk jk n NNk k N y n a H eeππ=<>=∑.Its coefficients of Fourier Series: 2()jk Nk k b a H eπ=(a)[][4]k x n n k δ∞=-∞=-∑.N=4, 14k a =.So 2314()524cos()44j k Nk k b a H e k ππ==-3165cos()42k b k π=-3.40 Solution: According to the property of fourier series: (a). )2cos(2)cos(20000000t Tka t kw a e a ea a k k t jkw k t jkw k k π==+='- (b). Because 2)()()}({t x t x t x E v -+=}{2k v k k k a E a a a =+='-(c). Because 2)(*)()}({t x t x t x R e +=2*kk k a a a -+='(d). k k k a Tjka jkw a 220)2()(π=='(e). first, the period of )13(-t x is 3T T ='then 3)(1)13(131213120dme m x T dt e t x T a m T jk T t T jk T k +'--'-'-'⎰⎰'=-'='ππTjkk m T jk T T jk T jk m T jk T ea dm e m x T e dm e e m x T πππππ221122211)(1)(1---------=⎥⎦⎤⎢⎣⎡==⎰⎰3.43 (a) Proof:（i ）Because ()x t is odd harmonic ,(2/)()jk T t k k x t a e π∞=-∞=∑,where 0k a = for everynon-zero even k.(2/)()2(2/)(2/)()2T jk T t k k jk jk T tk k jk T tk k T x t a ea e e a e ππππ∞+=-∞∞=-∞∞=-∞+===-∑∑∑It is noticed that k is odd integers or k=0.That means()()2Tx t x t =-+（ii ）Because of ()()2Tx t x t =-+,we get the coefficients of Fourier Series222/200/222(/2)/2/20022/2/200111()()()11()(/2)11()()(1)jk t jk t jk t T T T T T T k T jk t jk t T T T T Tjk t jk t T T k TT a x t e dt x t e dt x t e dtT T T x t e dt x t T e dt T T x t e dt x t e dt T T πππππππ-----+--==+=++=--⎰⎰⎰⎰⎰⎰⎰ 2/21[1(1)]()jk t T kT x t e dt T π-=--⎰It is obvious that 0k a = for every non-zero even k. So ()x t is odd harmonic ,(b)Extra problems:∑∞-∞=-=k kT t t x )()(δ, π=T(1). Consider )(t y , when )(jw H ist(2). Consider )(t y , when )(jw H isSolution:∑∞-∞=-=k kT t t x )()(δ↔π11=T , 220==Tw π(1).kt j k k tjkw k k e k j H a ejkw H a t y 20)2(1)()(0∑∑∞-∞=∞-∞===ππ2=(for k can only has value 0)(2).kt j k k tjkw k k e k j H a e jkw H a t y 20)2(1)()(0∑∑∞-∞=∞-∞===πππte e t j t j 2cos 2)(122=+=- (for k can only has value –1 and 1)。
信号与系统奥本海姆英文版课后答案chapter1
Chapter 1 Answers1.1 Converting from polar to Cartesian coordinates: 1.2 converting from Cartesian to polar coordinates:55j=, 22j e π-=,233jj eπ--=212je π--=, 41j j π+=, ()2221jj eπ-=-4(1)j j eπ-=, 411j jeπ+=- 12e π-= 1.3. (a) E ∞=4014tdt e∞-=⎰, P ∞=0, because E ∞<∞ (b) (2)42()j t t x eπ+=, 2()1t x =.Therefore, E ∞=22()dt t x +∞-∞⎰=dt +∞-∞⎰=∞,P ∞=211limlim222()TTTTT T dt dt TTt x --→∞→∞==⎰⎰lim11T →∞=(c) 2()t x =cos(t). Therefore, E∞=23()dt t x +∞-∞⎰=2cos()dt t +∞-∞⎰=∞,P ∞=2111(2)1lim lim 2222cos()TTTT T T COS t dt dt T Tt --→∞→∞+==⎰⎰(d)1[][]12nn u n x =⎛⎫⎪⎝⎭,2[]11[]4nu n n x =⎛⎫ ⎪⎝⎭. Therefore, E ∞=24131[]4nn n x +∞∞-∞===⎛⎫∑∑⎪⎝⎭P ∞=0，because E ∞<∞. (e) 2[]n x =()28n j e ππ-+, 22[]n x =1. therefore, E ∞=22[]n x +∞-∞∑=∞,P ∞=211limlim1122121[]NNN N n Nn NN N n x →∞→∞=-=-==++∑∑.(f) 3[]n x =cos 4nπ⎛⎫ ⎪⎝⎭. Therefore, E ∞=23[]n x +∞-∞∑=2cos()4n π+∞-∞∑=2cos()4n π+∞-∞∑,P ∞=1limcos 214nNN n NN π→∞=-=+⎛⎫∑ ⎪⎝⎭1cos()112lim ()2122NN n Nn N π→∞=-+=+∑ 1.4. (a) The signal x[n] is shifted by 3 to the right. The shifted signal will be zero for n<1, And n>7. (b) The signal x[n] is shifted by 4 to the left. The shifted signal will be zero for n<-6. And n>0. (c) The signal x[n] is flipped signal will be zero for n<-1 and n>2.(d) The signal x[n] is flipped and the flipped signal is shifted by 2 to the right. The new Signal will be zero for n<-2 and n>4.(e) The signal x[n] is flipped and the flipped and the flipped signal is shifted by 2 to the left. This new signal will be zero for n<-6 and n>0.1.5. (a) x(1-t) is obtained by flipping x(t) and shifting the flipped signal by 1 to the right. Therefore, x (1-t) will be zero for t>-2. (b) From (a), we know that x(1-t) is zero for t>-2. Similarly, x(2-t) is zero for t>-1, Therefore, x (1-t) +x(2-t) will be zero for t>-2. (c) x(3t) is obtained by linearly compression x(t) by a factor of3. Therefore, x(3t) will be zero for t<1. (d) x(t/3) is obtained by linearly compression x(t) by a factor of 3. Therefore, x(3t) will be zero for t<9.1.6 (a) x 1(t ) is not periodic because it is zero for t<0. (b) x 2[n ]=1 for all n. Therefore, it is periodic with a fundamental period of 1. (c) x 3[n1.7. (a)v ε[4])n --Therefore,()1[]vn xεis zero for 1[]n x >3. (b) Since x 1(t ) is an odd signal, ()2[]vn x εis zero for all values of t.(c) (){}11311[][][][3][3]221122v nnn n n u n u n x x x ε-⎡⎤⎢⎥=+-=----⎢⎥⎢⎥⎣⎦⎛⎫⎛⎫ ⎪ ⎪⎝⎭⎝⎭Therefore, ()3[]vn x εis zero whenn <3 and when n →∞.(d)()1554411()(()())(2)(2)22vttt t t u t u t x x x ee ε-⎡⎤=+-=---+⎣⎦Therefore,()4()vt x εis zero only whent →∞.1.8. (a) ()01{()}22cos(0)tt t x eπℜ=-=+l (b) ()02{()}cos()cos(32)cos(3)cos(30)4t t t t t x e ππℜ+==+l(c) ()3{()}sin(3)sin(32t t t t t x e e ππ--ℜ=+=+l(d) ()224{()}sin(100)sin(100)cos(1002t t t t t t t x e e e ππ---ℜ=-=+=+l1.9. (a) 1()t xis a periodic complex exponential.(b) 2()t x is a complex exponential multiplied by a decaying exponential. Therefore,2()t x is not periodic.（c ）3[]n x is a periodic signal. 3[]n x =7j n e π=j n e π.3[]n x is a complex exponential with a fundamental period of22ππ=. (d) 4[]n x is a periodic signal. The fundamental period is given by N=m(23/5ππ)=10().3m By choosing m=3. We obtain the fundamental period to be 10.(e) 5[]n x is not periodic. 5[]n x is a complex exponential with 0w =3/5. We cannot find any integer msuch that m(02wπ ) is also an integer. Therefore, 5[]n xis not periodic.1.10. x (t )=2cos(10t ＋1)-sin(4t-1)Period of first term in the RHS =2105ππ=.Period of first term in the RHS =242ππ= .Therefore, the overall signal is periodic with a period which the least commonmultiple of the periods of the first and second terms. This is equal to π . 1.11.x[n] = 1+74j n e π?25j n e πPeriod of first term in the RHS =1. Period of second term in the RHS =⎪⎭⎫ ⎝⎛7/42π=7 （when m=2）Period of second term in the RHS =⎪⎭⎫ ⎝⎛5/22ππ=5 (when m=1)Therefore, the overall signal x[n] is periodic with a period which is the least common Multiple of the periods of the three terms inn x[n].This is equal to 35.1.12. The signal x[n] is as shown in figure S1.12. x[n] can be obtained by flipping u[n] and thenShifting the flipped signal by 3 to the right. Therefore, x[n]=u[-n+3]. This implies that 1.13y (t)= ⎰∞-tdt x )(τ =dt t))2()2((--+⎰∞-τδτδ=⎪⎩⎪⎨⎧>≤≤--<2,022,12,0,t t tTherefore ⎰-==∞224dt E=2x 1[n-2]+ 5x 1[n-3] + 2x 1[n-4] The input-output relationship for S isy[n]=2x[n-2]+ 5x [n-3] + 2x [n-4](b) The input-output relationship does not change if the order in which S 1and S 2 are connected series reversed. . We can easily prove this assuming that S 1 follows S 2. In this case , the signal x 1[n], which is the input to S 1 is the same as y 2[n].Therefore y 1[n] =2x 1[n]+ 4x 1[n-1]= 2y 2[n]+4 y 2[n-1]=2( x 2[n-2]+21 x 2[n-3] )+4(x 2[n-3]+21x 2[n-4]) =2 x 2[n-2]+5x 2[n-3]+ 2 x 2[n-4]The input-output relationship for S is once againy[n]=2x[n-2]+ 5x [n-3] + 2x [n-4]1.16 (a)The system is not memory less because y[n] depends on past values of x[n].(b)The output of the system will be y[n]= ]2[][-n n δδ=0(c)From the result of part (b), we may conclude that the system output is always zero for inputs of the form ][k n -δ, k ∈ ?. Therefore , the system is not invertible .1.17 (a) The system is not causal because the output y(t) at some time may depend on future values of x(t). For instance , y(-π)=x(0).(b) Consider two arbitrary inputs x 1(t)and x 2(t).x 1(t) →y 1(t)= x 1(sin(t)) x 2(t) → y 2(t)= x 2(sin(t))Let x 3(t) be a linear combination of x 1(t) and x 2(t).That is , x 3(t)=a x 1(t)+b x 2(t)Where a and b are arbitrary scalars .If x 3(t) is the input to the given system ,then the corresponding output y 3(t) is y 3(t)= x 3( sin(t))=a x 1(sin(t))+ x 2(sin(t))=a y 1(t)+ by 2(t)Therefore , the system is linear.1.18.(a) Consider two arbitrary inputs x 1[n]and x 2[n].x 1[n] → y 1[n] =][001k x n n n n k ∑+-=x 2[n ] → y 2[n] =][02k x n n n n k ∑+-=Let x 3[n] be a linear combination of x 1[n] and x 2[n]. That is :x 3[n]= ax 1[n]+b x 2[n]where a and b are arbitrary scalars. If x 3[n] is the input to the given system, then the corresponding outputy 3[n] is y 3[n]=][03k x n n n n k ∑+-==])[][(2100k bx k ax n n n n k +∑+-==a ][001k x n n n n k ∑+-=+b ][02k x n n n n k ∑+-== ay 1[n]+b y 2[n]Therefore the system is linear.(b) Consider an arbitrary input x 1[n].Lety 1[n] =][01k x n n n n k ∑+-=be the corresponding output .Consider a second input x 2[n] obtained by shifting x 1[n] in time:x 2[n]= x 1[n-n 1]The output corresponding to this input isy 2[n]=][02k x n n n n k ∑+-== ]n [1100-∑+-=k x n n n n k = ][01011k x n n n n n n k ∑+---=Also note that y 1[n- n 1]=][01011k x n n n n n n k ∑+---=.Therefore , y 2[n]= y 1[n- n 1] This implies that the system is time-invariant.(c) If ][n x <B, then y[n]≤(2 n 0+1)B. Therefore ,C ≤(2 n 0+1)B.1.19 (a) (i) Consider two arbitrary inputs x 1(t) and x 2(t). x 1(t) → y 1(t)= t 2x 1(t-1)x 2(t) → y 2(t)= t 2x 2(t-1)Let x 3(t) be a linear combination of x 1(t) and x 2(t).That is x 3(t)=a x 1(t)+b x 2(t)where a and b are arbitrary scalars. If x 3(t) is the input to the given system, then the corresponding output y 3(t) is y 3(t)= t 2x 3 (t-1)= t 2(ax 1(t-1)+b x 2(t-1))= ay 1(t)+b y 2(t)Therefore , the system is linear.(ii) Consider an arbitrary inputs x 1(t).Let y 1(t)= t 2x 1(t-1)be the corresponding output .Consider a second input x 2(t) obtained by shifting x 1(t) in time:x 2(t)= x 1(t-t 0)The output corresponding to this input is y2(t)= t2x2(t-1)= t2x1(t- 1- t)Also note that y1(t-t)= (t-t)2x1(t- 1- t)≠y2(t)Therefore the system is not time-invariant.(b) (i) Consider two arbitrary inputs x1[n]and x2[n]. x1[n] →y1[n] = x12[n-2]x2[n ] →y2[n] = x22[n-2].Let x3(t) be a linear combination of x1[n]and x2[n].That is x3[n]= ax1[n]+b x2[n]where a and b are arbitrary scalars. If x3[n] is the input to the given system, then the corresponding outputy3[n] is y3[n] = x32[n-2]=(a x1[n-2] +b x2[n-2])2=a2x12[n-2]+b2x22[n-2]+2ab x1[n-2] x2[n-2] ≠ay1[n]+b y2[n]Therefore the system is not linear.(ii) Consider an arbitrary input x1[n]. Let y1[n] = x12[n-2]be the corresponding output .Consider a second input x2[n] obtained by shifting x1[n] in time:x 2[n]= x1[n- n]The output corresponding to this input isy 2[n] = x22[n-2].= x12[n-2- n]Also note that y1[n- n]= x12[n-2- n]Therefore , y2[n]= y1[n- n]This implies that the system is time-invariant.(c) (i) Consider two arbitrary inputs x1[n]and x2[n].x 1[n] →y1[n] = x1[n+1]- x1[n-1]x2[n ]→y2[n] = x2[n+1 ]- x2[n -1]Let x3[n] be a linear combination of x1[n] and x2[n]. That is :x3[n]= ax1[n]+b x2[n]where a and b are arbitrary scalars. If x3[n] is the input to the given system, then thecorresponding output y3[n] is y3[n]= x3[n+1]- x3[n-1]=a x1[n+1]+b x2[n +1]-a x1[n-1]-b x2[n -1]=a(x1[n+1]- x1[n-1])+b(x2[n +1]- x2[n -1])= ay1[n]+b y2[n]Therefore the system is linear.(ii) Consider an arbitrary input x1[n].Let y1[n]= x1[n+1]- x1[n-1]be the corresponding output .Consider a second input x2[n] obtained by shifting x1[n] in time: x2[n]=x 1[n-n]The output corresponding to this input isy 2[n]= x2[n +1]- x2[n -1]= x1[n+1- n]- x1[n-1- n]Also note that y1[n-n]= x1[n+1- n]- x1[n-1- n]Therefore , y2[n]= y1[n-n]This implies that the system is time-invariant.(d) (i) Consider two arbitrary inputs x1(t) and x2(t).x 1(t) →y1(t)= dO{}(t)x1x 2(t) →y2(t)= {}(t)x2dOLet x 3(t) be a linear combination of x 1(t) and x 2(t).That is x 3(t)=a x 1(t)+b x 2(t)where a and b are arbitrary scalars. If x 3(t) is the input to the given system, then the corresponding output y 3(t) is y 3(t)= d O {}(t) x 3={}(t) x b +(t) ax 21d O=a d O {}(t) x 1+b {}(t) x 2d O = ay 1(t)+b y 2(t)Therefore the system is linear.(ii) Consider an arbitrary inputs x 1(t).Lety 1(t)= d O {}(t) x 1=2)(x -(t) x 11t -be the corresponding output .Consider a second input x 2(t) obtained by shifting x 1(t) in time:x 2(t)= x 1(t-t 0)The output corresponding to this input isy 2(t)= {}(t) x 2d O =2)(x -(t) x 22t -=2)(x -)t -(t x 0101t t --Also note that y 1(t-t 0)= 2)(x -)t -(t x 0101t t --≠ y 2(t)Therefore the system is not time-invariant. 1.20 (a) Givenx )(t =jt e 2 y(t)=tj e 3x )(t =jte2- y(t)=tj e3-Since the system liner+=tj et x 21(2/1)(jt e 2-) )(1t y =1/2(tj e3+tj e3-)Thereforex 1(t)=cos(2t))(1t y =cos(3t)(b) we know thatx 2(t)=cos(2(t-1/2))= (j e -jte 2+jejt e 2-)/2Using the linearity property, we may once again write x 1(t)=21( j e -jt e 2+j e jt e 2-))(1t y =(je-jt e 3+je jt e 3-)= cos(3t-1)Therefore,x 1(t)=cos(2(t-1/2)))(1t y =cos(3t-1)1.21.The signals are sketched in figure S1.21.(f) Not period.1.26 (a) periodic, period=7.(b) Not period.(c) periodic, period=8.(d) x[n]=(1/2)[cos(3πn/4+cos(πn/4)). periodic, period=8. (e) periodic, period=16. 1.27 (a) Linear, stable(b) Not period. (c) Linear(d) Linear, causal, stable(e) Time invariant, linear, causal, stable (f) Linear, stable(g) Time invariant, linear, causal 1.28 (a) Linear, stable(b) Time invariant, linear, causal, stable (c)Memoryless, linear, causal (d) Linear, stable (e) Linear, stable(f) Memoryless, linear, causal, stable (g) Linear, stable1.29 (a) Consider two inputs to the system such that[][][]{}111.S e x n y n x n −−→=ℜand [][][]{}221.Se x n y n x n −−→=ℜNow consider a third inputx 3[n]= x2[n]+x 1[n]. The corresponding system outputWill be [][]{}[][]{}[]{}[]{}[][]33121212e e e e y n x n x n x n x n x n y n y n ==+=+=+ℜℜℜℜtherefore, we may conclude that the system is additive Let us now assume that inputs to the system such that andNow consider a third input x 3 [n]= x 2 [n]+ x 1 [n]. The corresponding system output Will betherefore, we may conclude that the system is additive (b) (i) Consider two inputs to the system such that()()()()211111Sdx t x t y t x t dt ⎡⎤−−→=⎢⎥⎣⎦and ()()()()222211S dx t x t y t x t dt ⎡⎤−−→=⎢⎥⎣⎦Now consider a third inputx 3[t]= x2[t]+x 1[t]. The corresponding system outputWill betherefore, we may conclude that the system is not additiveNow consider a third input x 4 [t]= a x 1 [t]. The corresponding system output Will beTherefore, the system is homogeneous.(ii) This system is not additive. Consider the fowling example .Let δ[n]=2δ[n+2]+ 2δ[n+1]+2δ[n] andx2[n]=δ[n+1]+ 2δ[n+1]+ 3δ[n]. The corresponding outputs evaluated at n=0 areNow consider a third input x 3 [n]= x 2 [n]+ x 1 [n].= 3δ[n+2]+4δ[n+1]+5δ[n]The corresponding outputs evaluated at n=0 is y 3[0]=15/4. Gnarly, y 3[0]≠]0[][21y y n +.ThisTherefore, the system is homogenous.1.30 (a) Invertible. Inverse system y(t)=x(t+4)(b)Non invertible. The signals x(t) and x 1(t)=x(t)+2πgive the same output (c) δ[n] and 2δ[n] give the same output d) Invertible. Inverse system; y(t)=dx(t)/dt(e) Invertible. Inverse system y(n)=x(n+1) for n ≥0 and y[n]=x[n] for n<0 (f) Non invertible. x (n) and –x(n) give the same result (g)Invertible. Inverse system y(n)=x(1-n) (h) Invertible. Inverse system y(t)=dx(t)/dt(i) Invertible. Inverse system y(n) = x(n)-(1/2)x[n-1] (j) Non invertible. If x(t) is any constant, then y(t)=0 (k) δ[n] and 2δ[n] result in y[n]=0 (l) Invertible. Inverse system: y(t)=x(t/2)(m) Non invertible x 1 [n]= δ[n]+ δ[n-1]and x 2 [n]= δ[n] give y[n]= δ[n] (n) Invertible. Inverse system: y[n]=x[2n]1.31 (a) Note that x 2[t]= x 1 [t]- x 1 [t-2]. Therefore, using linearity we get y 2 (t)= y 1 (t)- y 1 (t-2).this is shown in Figure S1.31(b)Note that x3 (t)= x1 [t]+ x1 [t+1]. .Therefore, using linearity we get Y3 (t)= y1 (t)+ y1 (t+2). this is2220201.34. (a) ConsiderIf x[n] is odd, x[n] +x [-n] =0. Therefore, the given summation evaluates to zero. (b) Let y[n] =x 1[n]x 2[n] .Theny [-n] =x 1[-n] x 2[-n] =-x 1[n]x 2[n] =-y[n]. This implies that y[n] is odd.(c)ConsiderUsing the result of part (b), we know that x e [n]x o [n] is an odd signal .Therefore, using {}1[][0][][]n n x n x x n x n ∞∞=-∞==++-∑∑22[][]e o n n n n x x ∞∞=-∞=-∞=+∑∑222[][][]e on n n n n n x x x ∞∞∞=-∞=-∞=-∞==+∑∑∑the result of part (a) we may conclude thatTherefore,(d)ConsiderAgain, since x e (t) x o (t) is odd,Therefore,1.35. We want to find the smallest N 0 such that m(2π /N) N 0 =2πk or N 0 =kN/m,where k is an integer, then N must be a multiple of m/k and m/k must be an integer .this implies that m/k is a divisor of both m and N .Also, if we want the smallest possible N 0, then m/k should be the GCD of m and N. Therefore, N 0=N/gcd(m,N).1.36．(a)If x[n] is periodic 0(),0..2/j n N T o ewhere T ωωπ+= This implies that 022o T kNT k T T Nππ=⇒==a rational number . (b)T/T 0 =p/q then x[n] =2(/)j n p q e π,The fundamental period is q/gcd(p,q) and the fundmental frequencyis(c) p/gcd(p,q) periods of x(t) are needed .1.37.(a) From the definition of ().xy t φWe have (b) Note from part(a) that()().xx xx t t φφ=-This implies that ()xy t φis even .Therefore,the odd part of ().xx t φis zero.(c) Here, ()().xy xx t t T φφ=-and ()().yy xx t t φφ= 1.38.(a) We know that /22(2)().t t δδ=V V Therefore This implies that(b)The plot are as shown in Figure s3.18.1.39 We have Also,2[][]0eon n n x x ∞=-∞=∑222[][][].e on n n n n n xx x ∞∞∞=-∞=-∞=-∞==+∑∑∑2220()()()2()().eoet dt t dt t dt t t dt x x x x x ∞∞∞∞-∞-∞-∞-∞=++⎰⎰⎰⎰0()()0.et t dt x x ∞-∞=⎰222()()().e ot dt t dt t dt xx x ∞∞∞-∞-∞-∞=+⎰⎰⎰0022gcd(,)gcd(,)gcd(,)gcd(,).T pp q p q p q p q q p q p pωωππ===/21lim (2)lim ().2t t δδ→∞→∞=V V V V(b) y(t)=x 2(t) is such a systerm . (c) No.For example,consider y(t) ()()ty t x d ττ-∞=⎰with ()()(1).x t u t u t =--Then x(t)=0for t>1,but y(t)=1 for t>1.1.41. (a) y[n]=2x[n].Therefore, the system is time invariant.(b) y[n]=(2n-1)x[n].This is not time-invariant because y[n- N 0]≠(2n-1)2x [n- N 0]. (c) y[n]=x[n]{1+(-1)n +1+(-1)n-1}=2x[n].Therefore, the system is time invariant .1.42.(a) Consider two system S 1 and S 2 connected in series .Assume that if x 1(t) and x 2(t) arethe inputs to S 1..then y 1(t) and y 2(t) are the outputs.respectively .Also,assume thatif y 1(t) and y 2(t) are the input to S 2 ,then z 1(t) and z 2(t) are the outputs, respectively . Since S 1 is linear ,we may writewhere a and b are constants. Since S 2 is also linear ,we may write We may therefore conclude thatTherefore ,the series combination of S 1 and S 2 is linear. Since S 1 is time invariant, we may write andTherefore,Therefore, the series combination of S 1 and S 2 is time invariant.(b) False, Let y(t)=x(t)+1 and z(t)=y(t)-1.These corresponds to two nonlinear systems. If these systems are connected in series ,then z(t)=x(t) which is a linear system.(c) Let us name the output of system 1 as w[n] and the output of system 2 as z[n] .Then The overall system is linear and time-invariant. 1.43. (a) We haveSince S is time-invariant.Now if x (t) is periodic with period T. x{t}=x(t-T). Therefore, we may conclude that y(t)=y(t-T).This implies that y(t) is also periodic with T .A similar argument may be made in discrete time . (b)1.44 (a) Assumption : If x(t)=0 for t<t 0 ,then y(t)=0 for t< t 0.To prove That : The system is causal.Let us consider an arbitrary signal x 1(t) .Let us consider another signal x 2(t) which is the same as x 1(t)fort< t 0. But for t> t 0 , x 2(t) ≠x 1(t),Since the system is linear, Since ()()120x t x t -=for t< t 0 ,by our assumption =()()120y t y t -=for t< t 0 .This implies that()()12y t y t =for t< t 0 . In other words, t he output is not affected by input values for 0t t ≥. Therefore, thesystem is causal .Assumption: the system is causal . To prove that :If x(t)=0 for t< t 0 .then y(t)=0 for t< t 0 .Let us assume that the signal x(t)=0 for t< t 0 .Then we may express x(t) as ()()12()x t x t x t =-, Where()()12x t x t = for t< t 0 . the system is linear .the output to x(t) will be()()12()y t y t y t =-.Now ,since the system is causal . ()()12y t y t = for t< t 0 .implies that ()()12y t y t = for t< t 0 .Therefore y(t)=0 for t< t 0 .(b) Consider y(t)=x(t)x(t+1) .Now , x(t)=0 for t< t 0 implies that y(t)=0 for t< t 0 .Note that the system is nonlinear and non-causal .(c) Consider y(t)=x(t)+1. the system is nonlinear and causal .This does not satisfy the condition of part(a). (d) Assumption: the system is invertible. To prove that :y[n]=0 for all n only if x[n]=0 for all n . Consider[]0[]x n y n =→. Since the system is linear :2[]02[]x n y n =→.Since the input has not changed in the two above equations ,we require that y[n]= 2y[n].This implies that y[n]=0. Since we have assumed that the system is invertible , only one input could have led to this particular output .That input must be x[n]=0 .Assumption: y[n]=0 for all n if x[n]=0 for all n . To prove that : The system is invertible . Suppose that andSince the system is linear ,By the original assumption ,we must conclude that 12[][]x n x n =.That is ,any particular y 1[n] can be produced that by only one distinct input x 1[n] .Therefore , the system isinvertible.(e) y[n]=x 2[n].1.45. (a) Consider ,and()222()()s hx x t y t t φ→=.Now, consider ()()()312x t ax t bx t =+. The corresponding system output will be Therefore, S is linear .Now ,consider x 4(t)=x 1(t-T).The corresponding system output will beClearly, y 4(t)≠ y 1(t-T).Therefore ,the system is not time-invariant.The system is definitely not causal because the output at any time depends on future values of the input signal x(t).(b) The system will then be linear ,time invariant and non-causal.1.46. The plots are in Figure S1.46.1.47.(a) The overall response of the system of Figure P1.47.(a)=(the response of the system to x[n]+x 1[n])-the response of the system to x 1[n]=(Response of a linear system L to x[n]+x 1[n]+ zero input response of S)- (Response of a linear system L to x 1[n]+zero input response of S)=( (Response of a linear system L to x[n]).。
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Clearly, is just a shifted version of . Therefore,x(t)may be recovered from y(t) simply by multiplying y(t) by . There is no constraint that needs to be placed on to ensure that is recoverable from .
Chapter8 Answers
8.1Using Table 4.1, take the inverse Fourier transform of . This gives .
Therefor Y( ) of y(t) is given by
TheFourier transformof this signal is
.
Thisimplies that is zero for . When is passed through a lowpass fiter with cutoff frequency ,the output will clearly be zero .Therefore =0.
8.4Consider the signal
Ifthissignal is passed through a lowpass filter with cutoff frequency 400 ,then the output
will be
.
8.5The signal is as shown in Figure S8.5
is as shown in Figure S8.6
TheFourier transformof is also shown in Figure S8.6.Clearly,if we want to recover from ,then we have to pass through an ideal lowpass filter with gain 4 and cutoff frequency .Therefore ,A=4.
8.7 In Figure S8.7 ,we show , ,and .We also show a polt ofTheFourier transformof ,then we need to ensure that (1) , and (2) an ideal lowpass filter with passband gain of 2 and a cutoff frequency of is used to filter .
Therefore , A should at least be .The modulation index corresponding to the smallest permissible value of A is
=
8.6Let usdenote the Fourier transform of by . This will be rectangular pulse which is nonzero only in the range . Taking TheFourier transformof the first equation given in the problem ,we have
8.8(a) From Figure S8.8,it is clear that is conjugate-symmetric .Therefore, is
real.
(b) This part of the problem explores the demodulation of SSB signals through synchronous demodulation. This idea is explored in more detail in problem 8.29.
Figure S8.5
The envelope of the signal is as shown in Figure S8.5.Clearly,is we want to use asynchronousdemodulationto recover the signal ,we need to ensure that A is greater than the height of the highest sidelobe (see Figure S8.5).Let us now determine the height of the highest sidelobe.The first zero-crossing of the signal occurs at time such that
Similarly , the second zero–crossing happens at time such that
The highest sidelobe occurs at time .that is ,at time . At this time, the amplitude of is
(b) We know that
TheFourier transform of is as shown in Figure S8.2
If we want to prevent the two shifted replicas of from multiplied by , the output will be