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2.2.LinearTime-InvariantSystems(WHYAbasicfact:IfweknowtheresponseofanLTItosomeinputs,weactuallyknowtheresponsetomanyKeypointsofSignalsdecomposition:basicsignalCHAPTERLinearTime- ResponseResponsesynthesis:basicresponse(impulse2.2.LinearTime-InvariantSystems(WHYAbasicfact:IfweknowtheresponseofanLTItosomeinputs,weactuallyknowtheresponsetomanyKeypointsofSignalsdecomposition:basicsignalResponseResponsesynthesis:basicresponse(impulse2.12.1Discrete-timeLTIsystem:TheconvolutionTheRepresentationofDiscrete-timeSignalsinTermsofImpulses2.12.1Discrete-timeLTIsystem:TheconvolutionTheRepresentationofDiscrete-timeSignalsinTermsofImpulses.1Decompositionofadiscrete-timesignalintoaweightedsumofshifted/.1Decompositionofadiscrete-timesignalintoaweightedsumofshiftedIfx[n]=u[n],x[n][nkkx[n]x[k][nk]k

TheDiscrete-timeUnitImpulseResponseandtheConvolutionSumRepresentationofLTISystems(1)UnitImpulse(Sample)UnitUnitimpulseTheDiscrete-timeUnitImpulseResponseandtheConvolutionSumRepresentationofLTISystemsUnitImpulse(Sample)UnitUnitimpulseGivenGiventheUnitImpulseResponse:

IFn h

[n-k]

x[k][n-k]∑x[k][n-k]

x[n]

GivenGiventheUnitImpulseResponse:IFd h

i i i

i UnitimpulseUnitimpulse

x[n]

x[k][nk

k

y[n]

x[k kk ¥

¥x[n]¥

n¥

kFigure

y[n]x[1]h1[n]x[0]h0[n]Figure Example2.1(InExample2.1(Ingraphic21 01234 01234nnn

+

222

2[n2[n

2y[n]x[0]h0[n]2y[n]x[0]h0[n] 134n2 Ifx[n],h[n]isy[n]x[k]h[nk]kConvolution y[n]=x[n]*(3)CalculationofConvolution Independentvariablereplace:x[n]x[k],h[n]h[k]Four

TimeInversalTimeShifth[k]h[-k]h[n-Multiplication:

y[n]

k

k +

2

ExampleExampleExampleExampleCalculationofConvolutionExampleConvolutionSumofLTIInput:Input:x[n]x[k]kk]Output:y[n]=y[n]x[k]h[nk

kIfx[n],h[n]isIfx[n],h[n]isConvolutiony[n]=x[n]*Independentvariable x[k],h[n] TimeInversalTimeShift:Four

+

2.2Continuous-timeLTI2.2Continuous-timeLTIh(t)is2.2.1TheRepresentationofContinuous-timeSignalsinTermsofImpulses δ(t(t)(t)(t),0t1t0ExampleExampleExampleExampleCalculationofConvolutionExampleConvolutionSumofLTI¥ ?(t)?(t)kTheconvolutionh(t)is2.2.1TheRepresentationofContinuous-timeSignalsinTermsofImpulses δ(td(t)=,0£t£D1fiD0………x(t)limx(k)(t0kx(t)x( WehavetheInInanother

x(t)

x(t)

x(t)x(t)

x(t)

isactuallyasumofdelayedx(t),u(t)x()(t01(ttt(

222Th nin -timeUnitimpulseResponseandtheconvolutionIntegralRepresentationofLTISystems1UnitImulseResxt= TheConvolutionofLTIInInanother¥ ¥

x(t)=

¥=x(t)¥=

d(t-x(t)isactuallyasumofdelayedxx(t)=,u(t)=¥==1d(t-¥0=t()d h(t)limh(t)limh(t)

(t)??

k)

x(tx(t)x(k)k(tkkk(t

x(k)response{

t =

?t

?tx(t)

y(t)

)h(t )d(Input:Sumofunit (Output:Sumofunitimpulses222Th nin -timeUnitimpulseResponseandtheconvolutionIntegralRepresentationofLTISystems1UnitImulseResxt=d (2)TheConvolutionofLTIDDD)d(t)=limdDh(t)=limhDfiDDfidhdD(t)fihDdhdD(t-kD)fihD(t-? ?(t)Becausex(t)x()(tWecany(t)x()h(t y(t)=x(t)* (ConvolutionIntegral Dfi

?t)fiDfi

?tx(t)

x(t)d(t-t)dty(t)=-¥x()h(t-(Input:Sumofunit(3)CalculationofConvolution(3)CalculationofConvolutionFour

(-)h(-TimeShift:(t-)h(t- x()h(t-

y(t)

Independentvariable

,h(t)

Transformationofin

h(-

h(t- x()h(t-tIntegral

y(t)

)h(t )d (Output:Sumofunitimpulses

01

)

ExampleExample (SimilartoExample 1

t

y(t)0d

ea,0

t 1

y(t)ea0

aExample (Anothersolutiony(t)x(t)*h(t)eatu(t)*u(t),aeau(

x(t

h(t [ea0

1a

Because

Wecan y(t)=-¥x()h(t- y(t)=x(t)*Example2.7(Calculateitbyyourself!)(SimilartoExample2.4)Example2.8(Calculateitbyyourself!)(SimilartoExample2.5)ExperimentExperimentdemonstrationforConvolutionIntegral(3)(3)CalculationofConvolutionFour

Inverse:d(- fih(-TimeShift:d(t- fih(t- -

y(t)=-

Independentvariable fiTransformationoftin fih(t-(Input:SumofunitOutut:SumofunitimulseresD-

x[n]

k

k

y[n]

k

ky[n]=x[n]*ConvolutionC-x(t)

y(t)

y(t)=x(t)*// tIntegral

y(t)

x()h(t- Four

Independentvariablereplace:x[n]x[k],h[n]h[k]TimeInversalTimeShift:h[k]h[-k]h[n-k]CalculationofConvolutionSum/ConvolutionCalculationofConvolutionSum/Convolution

y[n]

kFour

Independentx(t)x(),h(t)h()Transformationofinh():h()h(-)h(t- x()h(t-

y(t)

)d

01

t

01

¥ -¥<t<¥,t< y(t)=0dt=

t> [n]x[n]x[n][n]h[n]

k]

—C-A[nk]x[n]Ax[nk(t)h(t)h(t(t

)h(t)

h(t

(t)x(t)x(t(t)x(t)x(t

y(t)

e-atdt=(1-e-ata0aConvergenceConvergenceofu[n]u[n]

Notu[n]1

u[n]{u[n1]u[n]}

?NotC-u(t)u(t)

?Notu(t)1

u(t)

u(t)}

?NotExample (Anothersolutiony(t)=x(t)*h(t)=e-atu(t)*u(t),a>¥ x()t=[e-01

h(t- a2.32.3PropertiesofLTIOutputResponseofLTIy[n]=x[n]y[n]=x[n]y[n]x[n]*h[n]x[k]h[nk y(t)=x(t)Convolution forLTIsItsoutputresponsecanbeobtainedbyconvolutionItcanbecompletelycharacterizedbyitsUnitImpulsey(t)

x(t)*h(t)

2.3.12.3.1TheCommutativeDiscrete x[n]*h[n]=h[n]Continuoustime:x(t)*h(t) h(t)Howtoh y(t)=x(t)hy(t)=h(t)Example2.7(Calculateitbyyourself!)(SimilartoExample2.4)Example2.8(Calculateitbyyourself!)(SimilartoExample2.5)ExperimentExperimentdemonstrationforConvolutionIntegralTheDistributiveProDiscretex[n]*{h1[n]+h2[n]}=x[n]*h1[n]+x[n]*h2[n]Continuoustime:x(t)*{h1(t)+h2(t)}=x(t)*h1(t)+x(t)y(t)=x(t)y(t)=x(t)y(t)=x(t)y(t)=x(t)*h1(t)+x(t)x(Input:SumofunitOutut:Sumofunitimulseres x[n]=

LTIy[n]=

x(t)

y[n]=x[n]*ConvolutionIy(t)=+¥x(t)h(t-y(t)=x(t)*ConvolutionExampleExamplex[n]

(12

u[n]

2nu[n],h[n]

n )u[n]n

x2[n]

y[n]

(1[n

x2[n])*y[n]

y2[n]Example2.3Exampley1[n]x1[n]*y2[n]x2[n]*

Independentvariablereplace: fix[k],h[n] fih[k]TimeInversalTimeShift: fih[-k] fih[n-k] + Four

fix(t),h(t) Transformationoftinh(t): fih(-t) fih(t- x(t)h(t-t)TheAssociativeProDiscretex[n]*{h1[n]

Continuous

*{1(t)

2(t)}={x(t)

1(t)}

Howy(t)=x(t)*{h1(t)y(t)=x(t)*h1(t)h1(t)

Integrating:y(t)=-

LTIsstemwithandwithoutMemorylessDiscretetime: y[n]=kx[n],h[n]=k[n]Continuoustime:y(t)=kx(t),h(t)=k(t)x(t)y(x(t)y(t)kx(t)x(t)k(t)(t)kImplythat:x(t)*(t)=x(t)andx[n]

y[n]

kx[n]

x[n]k

(t)*h(t)=h(tAd[n-k]*x[n]=Ax[n-k(t-)*h(t)=h(t-C-C-

d(t)*x(t)=x(t2.3.52.3.5ofLTIsOriginalsystem:Reversesystem:h(t)xh(t)

x(t)

x(t)(t)x(t)(t)So,fortheinvertibleh(t)*h1(t)=(t)orh[n]d(t-t)*x(t)=x(t-t)h(t)h(t)(tt0

t0yy(t)x(t) (tt0)x(tt0

t0)1t

h1(t)

(tt0

ConvergenceConvergenceofu[n]*u[-n]= Notu[n]*1=u[n]*{u[n-1]+u[-n]}=?Notu(t)*u(-t)=?Notu(t)*1=u(t)*{u(t)+u(-t)}=?Not

ififh[n]h1[n][n]u[n]u[nu[n]{[n][n[n][nExample2.12(Example2.12(累加器y[n]x[k]u[nk]kx[k]1x[k]nku[nk]ku[nkkn

2.32.3PropertiesofLTIOutputResponseofLTI y(t)=x(t)Convolutiony(t)=x(t)*h(t)=-¥x(t)h(t-

u(t)yy(t)x(t)u(t)ttt(t)du(t)(t(t)du(t)(ty(t)1

u(t)

(t)

1t Example積分器Example積分器

2.3.12.3.1TheCommutative x[n]*h[n]=h[n]Continuoustime:x(t)*h(t) h(t)Howto y(t)=x(t)y(t)=h(t)x[k]u[nx[k]u[nk]kDiscretetimesystemsatisfythecondition:h[n]=0forn<0Continuoustimesystemsatisfythecondition:y[n] h[n]=0for TheDistributiveProDiscretex[n]*{h1[n]+h2[n]}=x[n]*h1[n]+x[n]*h2[n]Continuoustime:x(t)*{h1(t)+h2(t)}=x(t)*h1(t)+x(t)Howtoxxh1y(t)=x(t)*h1(t)+x(t)2.3.72.3.7StabilityforLTIDefinitionofstability:Everyboundedinputproducesaboundedoutput.Discretetime y[n]

k

x[

]h[n

k]

or

k

x[n

k]h[k |y[n]

|

k]

B|

|

|y[n]|Example1Examplex[n]=(21

y[n]=([n+x2[n])*Example2.3ExampleIfIf|x[n]|<B,theconditionfor|y[n]|<A|k

isstable y(t)

,

,

)h(y2[n]=x2[n]*|y(t)

)

B

)|

|y(t)|If|x(t)|<B,theconditionfor|y(t)|<A|h()|disTheAssociativeProDiscretex[n]*{h1[n]*h2[n]}={x[n]*h1[n]}Continuousx(t)*{1(t)*2(t)}={x(t)*1(t)}*HowtoProveh1(t)y(t)=x(t)*{h1(t)y(t)=x(t)*h1(t)ExampleExamplePuretimeshift y[n]

y(t)

t0

h(t)

t0Note:(2.89)shouldnotbecommonlyn

kt

y(t)

h(t)

u(t)LTIsstemwithandwithoutMemorylessDiscretetime: Continuoustime:y(t)=kx(t),h(t)=kd(t) forProertiesofLTIDiscrete Continuous(1)x[n]*h[n]=h[n] x(t)*h(t) h(t)2xn*{h1n+h2 x(t)

h(t)=k|h[k]|k|h()|d

h[n]=0forn<0h[n]*h1[n]=[n]

h(t)=0fort<0h(t)*h1(t)=(t)2.3.52.3.5ofLTIsOriginalsystem:Reversesystem: x(t)

So,fortheinvertibleh(t)*h1(t)=d(t)orh[n]TypicalTypicalLTISystemanditsUnitImpulseDiscrete Continuous

Identityht=

x[n][n]

y(t)

x(t)(t)

Gain y[n]

x[n]K[n]

y(t)

x(t)

(t)

yy[n]x[n][nn]x[nn00y(t)x(t)(tt)x(tt y(t)=x(t-t0yy(t)=x(t)*(t-t0)=x(t-t0 h(t)*h1(t)= =d(t-t0)*1t= =y[n]

x[n]h[n]

x[knkn

y(t)

x(t)h(t)

t1storder 1storderth[n]=[n]-[n- x[n]([n][nx[n]x[ny(t)x(t)d(t)dx(t)(t+t0 s[n]u[n]Unitstepresponses[n]h[n]2.3.8TheUnitResonseofLTIsD-Unitimpulses(t)u(t)h(t)h(t)u(t)ifh[n]*h1[n]=x[k]1+x[k]u[n-k]k[n] RelationshipRelationshipbetweenh[n]andD-

s[n]

nkn

h(1)[n],

s[n]

s[n]

tC-ts(t)

h(

h

(t), h(t)

s h(t)=yy(t)=x(t) h(t)*h1(t)= d(t)=y(d(t)=y(t==2.3.9ConvolutioninteralwithSinularit(1)x(t)* xx

*

t0)

t0x

t

x

x(t)*

'(t)

(5)(5)x(t)*u x(1) tx(6)x(t)*h(t)x'(t)h(1)(t) Proofxt)

h(t)

x(t)

h(t)

u(t)

'(t)[x(t)

'(t)][h(t)

u(t)]'x(t)'

(t)2.3.6 forLTIsDiscretetimesystemsatisfythecondition:h[n]=0forn<0Continuoustimesystemsatisfythecondition:

h[n]=0forhh(t)u(t)u(th(t)1x(t)110t1t101

y(t)

x( )d2.3.72.3.7StabilityforLTIDefinitionofstability:Everyboundedinputproducesaboundedoutput.Discretetime y[n]=x[k]h[n-k],or,x[n-k]h[kk=- k=-

|y[n]

|

x[n-k]||h[k]|<B

②Usingthepropertiesof(t)

h'(t) 2 011

1 h'(t)

(t)

2 y(t)

x(1)

x(1)

1

y(t)t1t1

x(1)(t)t1

x(1)

1)

1

1

|

|y[n]|<ConvolutionConvolutionIfIf|x[n]|<B,theconditionfor|y[n]|<A|

isstable y(t)=-¥x(t)h(t-t)dt,or,-¥x(t-Convolution|y(t)

-¥|h()| |y(t)|<If|x(t)|<B,theconditionfor|y(t)|<ADiscrete Continuousy[n]x[n]y[kn]x[kn]y[nn0]x[nn0]

y(t)x(t)h(t)y(kt)x(kt)h(t)y(tt0)x(tt0)h(t)x(t)h(t)y(tx(tt)h(tt)y(t2t000x(kt)h(kt)1y(ktk

isstableKeKewordsforChaterUnitImpulsePuretimeshift y(t)=x(t-t0 h(t)=d(t-t0Note:(2.89)should

tbecommonly

y[n]=t

CausalLTISystemsDescribedbyLinearConstant-CoefficientDifferentialandDifferenceNMDiscretetimesystem:DifferenceNMk

k]

bkk

k Continuoustimesystem: NNdky(t)dtkkdxkdtk ConstantHowtogetoutputoftheLTIsystemlikey(t)

x(tt

h(u(t))LinearConstant-CoefficientDifferenceAgeneralNth-orderlinearconstant-coefficientdifferenceNN

k]

bkMM

k RecursiveaNy[nN]aN1y[n(N

L

a0

(M1)]L

initialy[-1],……,y[-(N- (Nvalues forProertiesofLTIDiscrete Continuous(1)x[n]*h[n]=h[n]*x[n] x(t)*h(t)= h(t)*x(t)2xn*{h1n+h2n x(t)*{h1(t)+h2(t)} h(t)=k

h[n]=0forn<0

h(t)=0fort<0

y[n]

x[nkMk0M

a0 Nonrecursivennh[n]

0n FiniteImpulse

bkMM

k]

NN

k]Recursive

Determinethesystemresponse(output)recursivelyTypicalLTISystemanditsUnitImpulseDiscrete ContinuousIdentity ht=d Gain y(t)=x(t)* (t)=Time sConditionConditionoInitialResty[n]=x[n]*h[n]=x[k

y(t)=x(t)*h(t)=

yy(t)=x(t)*dd(t)=(ConditionofInitialAlinearsystemiscausalifandonlyifitsatisfiestheconditionofinitialrest:x(n)ny(n)nSupposesystemiscausal.Showthat(*)Suppose(*)holds.Showthatthesystemis2.3.82.3.8TheUnitResonseofLTIsD-Unitimpulses(t)=u(t)*h(t)=h(t)ExampleExampleThey[nThey[n]1y[n1]x[n]x[n]K[n]Recursiveequationy[n]Initialcondition

x[n]2

x(n)

n(ConditionofInitial

y(n)

nRelationshipRelationshipbetweenh[n]andnD- s[n]=n

h[k]=h(-1)[n],tth()dt=h-1(t), h(t)=ss(t)=-n

y(n)n

x[0]2

n

2

y[0]12n

x[2]2M

2

x[n]2

(1)n2

K[n]

y[n]

(1)n2

Theimpulse

(1)2

nfiniteImpulseResponse

Recursive

bk

k]

k]InfiniteImpulseResponse Nonrecursivey[n]

Mk0M

kFiniteImpulse 2.3.9ConvolutioninteralwithSinularitx(t)*d =x xt*d(t-t0)=x(t-t0 xt- =xt-t1- x(t)*d'(t)=x2.4.22.4.2LinearConstant-CoefficientDifferentialAgeneralNth-orderlinearconstant-coefficientdifferential d

y(t)

(t)

dtk

bk

dtkN y(N)(t)N

aN

y(N1)(t)L

a1y'(t)

a0y(t)

x(M)(t)

x(M1)(t)L

x'(t)

x(t)M1andM1y(t0),y’(t0),……,y(N- (Nvaluesxxt(5)(5)x(t)*u=x(-1)(6)x(t)*h(t)=x'(t)*h(-1)SolutionoftheN-thorderlinearconstantcoefficientyy(t)1a0Mk0y(t)y(t)y*(t)

Proofxt)h(t)=x(t)*h(t)*u(t)*d'=[x(t)*'(t)]*[h(t)*u(t)]'=x(t)h(1)(t)'HowHowtogettheHomogeneous y(t)SolvethehomogeneousdifferentialNk Nk

y(t)k

RootsofthecharacteristicNakki(i1,2,L,Nh(th(t)=u(t)-u(t-1t11x(t)0

y(t)

x()h(t-HowtogettheParticular

y*

isdependantonboththeexcitationsign andthesystembehavior.y*h'(t) 2 1 h'(t)=d(t)-d(t-t112y(t)=x(-1)(t)-x(-1)(t-t121

y(t)1

x(-1)ttt -x(-1)(t-1) 21Example①GettheHomogeneous

y(t)②Gettheparticular

y(t)

y(t)

Auxiliaryconditiontodeterminecomleteltheinput-outputrelationship–Initialrest.LTI

x(t0)y(t0)

tt0tt00(ConditionofInitial0y(t0)

y(t0)

y(t0

L

y(N1)(t)21Systemyy(t)y(t)y*(t)NaturalForcedGeneralresponse=Zero-state+Zero-Input=Generalresponse=Zero-state+Zero-Input=Forced+NaturalConvolutionConvolution.. .. BlockDiagramRepresentationsofFirst-orderSystemsDescribedbyDifferentialandDifferenceEquationDiscretetimesystem:DifferenceNNk

bkMkM

BasicelementsforadiscretetimesystemAnMultiplicationbyaC.Anunit ConvolutionBasicMultiplicationMultiplicationbyaaUnitDiscrete Continuous

y(-t)?x(-t)*h(t)y(kt)?x(kt)*h(t)y(t-t0)=x(t-t0)x(-t)*h(-t)=y(-tx(kt)*h(kt)=1y(ktk x(t-t)*h(t-t)=y(t-2t) y[n]+ay[n-KeKewordsforChaterContinuoustime d

y(t)

(t)

dtk

bk

dtkBasicAnMultiplicationbyaAn(differentiator)CausalLTISystemsDescribedbyLinearConstant-CoefficientDifferentialandDifferenceDiscretetimesystem:Difference k

k

Continuoustimesystem:Differential BasicBasicMultiplicationMultiplicationbyax(t)ax(t)aNNkdxk(ConstantHowtogetoutputoftheLTIsystemlike

y(t)

ay(t)

bx(t)LinearConstant-CoefficientDifference k

k

RecursiveaNy[n-N]+aN-1y[n-(N-1)]+L+a1y[n-1]+a0 (M-1)]+L+ initialReviewReviewforChaptersystemUnitImpulseConvolutionLTIsystemDescribedbyLinearConstant-CoefficientDifferenceandDifferentialEquation(LCCDE)

(ConditionofInitialBlockDiagramy[-1],……,y[-(N- (NvaluesReviewfory[n]=x[n]Reviewfory[n]=x[n]y(t)=x(t)x[n]x[n]x[k][nkkResponsey[n]x[k]h[nkx(t)x()(ty(t)x()h(tk

x[n-kMk=0 Nonrecursiveh[n]

0£n£ FiniteImpulse N≥1:y[n]=k

k

x(t)

y(t)

x(t)*h(t)y[n]

x[n]* (t1,t2

[N1,

N2

(t3,t4

[N3

N4

(t1t3,

t4[N1

N3,N2N4Causal(right- two-sideornotes1t,tz0,nnes2tu(t)1es1t,Re[s]]s1z1zn, 200Recursive

Determinethesystemresponse(output)recursivelyPropertiesPropertiesofLTIDiscrete Continuous(1)x[n]*h[n]=h[n] x(t)*h(t) h(t)2xn*{h1n+h2 x(t)

h(t)=k |h[k]|k|h()|d

h[n]=0forn<0h[n]*h1[n]=[n]

h(t)=0fort<0h(t)*h1(t)=(t)ConditionConditionoInitialRestSolutionSolutionforDifferenceRecursiveequationyy[n]x[n]1y[n2Initialcondition

=(ConditionofInitial x(n)

n

y(n)

n(ConditionofInitialx(n)=n<y(n)=x(n)=n<y(n)=n<Supposesystemiscausal.Showthat(*)Suppose(*)holds.ShowthatthesystemisHomeworkHomeworkforChapterPartI(卷積和2.3,2.5,PartII(卷積積分):2.10(a),Part 2.1,2.25(b),PartIV(差分方程求解 , , 入理解ExampleExampleRecursiveequationInitialcondition

2

y[n-(LTI, x(n)= n<(ConditionofInitial y(n)= n<n< y(n)=n=0 n=1

y[0]=121n= 2M

1)222 2

nn1 y[n]=()n2

Theimpulse

2

nfiniteImpulseResponse Recursive k

k

InfiniteImpulseResponse M x[n-kMk=0FiniteImpulseResponse2.4.22.4.2LinearConstant-CoefficientDifferentialcofficientdiffrential dk

dx

=dtdt

dtkaNy(N)(t)+ y(N-1)(t)+L+a1y'(t)+a0=bMx(M)(t)+ x(M-1)(t)+L+bx'(t)+b0 andinitialy(t0),y’(t0),……,y(N- (NvaluesSolutionoftheN-thorderlin

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