数字信号处理基于计算机的方法第三版matlab程序Word格式.docx
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a=input（'
Typeinrealexponent='
b=input（'
Typeinimaginaryexponent='
c=a+b*i;
K=input（'
Typeinthegainconstant='
N=input（'
Typeinlengthofsequence='
n=1:
N;
x=K*exp（c*n）;
%Generatethesequence
stem（n,real（x））;
%Plottherealpart
title（'
Realpart'
disp（'
PRESSRETURNforimaginarypart'
stem（n,imag（x））;
%Plottheimaginarypart
Imaginarypart'
%Program2_3
%Generationofrealexponentialsequence
Typeinargument='
n=0:
x=K*a.^n;
stem（n,x）;
title（['
\alpha='
num2str（a）]）;
%Program2_4
%SignalSmoothingbyaMoving-AverageFilter
1:
x=s+d'
plot（m,d,'
r-'
m,s,'
b--'
m,x,'
g:
'
）
ylabel（'
legend（'
d[n]'
'
s[n]'
x[n]'
M=input（'
Numberofinputsamples='
b=ones（M,1）/M;
y=filter（b,1,x）;
plot（m,s,'
m,y,'
y[n]'
xlabel（'
）
%Program2_5
%IllustrationofMedianFiltering
N=input（'
MedianFilterLength='
a=rand（1,R）-0.4;
b=round（a）;
%Generateimpulsenoise
%Generatesignal
x=s+b;
%Impulsenoisecorruptedsignal
y=medfilt1（x,3）;
%Medianfiltering
subplot（2,1,1）
stem（m,x）;
axis（[050-18]）;
n'
ImpulseNoiseCorruptedSignal'
subplot（2,1,2）
stem（m,y）;
OutputofMedianFilter'
%Program2_6
%IllustrationofConvolution
Typeinthefirstsequence='
Typeinthesecondsequence='
c=conv（a,b）;
M=length（c）-1;
M;
outputsequence='
disp（c）
stem（n,c）
%Program2_7
%ComputationofCross-correlationSequence
x=input（'
Typeinthereferencesequence='
y=input（'
%Computethecorrelationsequence
n1=length（y）-1;
n2=length（x）-1;
r=conv（x,fliplr（y））;
k=（-n1）:
n2'
stem（k,r）;
Lagindex'
v=axis;
axis（[-n1n2v（3:
end）]）;
%Program2_8
%ComputationofAutocorrelationofa
%NoiseCorruptedSinusoidalSequence
N=96;
x=cos（pi*0.25*n）;
%Generatethesinusoidalsequence
d=rand（1,N）-0.5;
%Generatethenoisesequence
y=x+d;
%Generatethenoise-corruptedsinusoidalsequence
r=conv（y,fliplr（y））;
%Computethecorrelationsequence
k=-28:
28;
stem（k,r（68:
124））;
%Program3_1
%Discrete-TimeFourierTransformComputation
%Readinthedesirednumberoffrequencysamples
k=input（'
Numberoffrequencypoints='
%Readinthenumeratoranddenominatorcoefficients
num=input（'
Numeratorcoefficients='
den=input（'
Denominatorcoefficients='
%Computethefrequencyresponse
w=0:
pi/（k-1）:
pi;
h=freqz（num,den,w）;
%Plotthefrequencyresponse
subplot（2,2,1）
plot（w/pi,real（h））;
grid
\omega/\pi'
subplot（2,2,2）
plot（w/pi,imag（h））;
subplot（2,2,3）
plot（w/pi,abs（h））;
MagnitudeSpectrum'
Magnitude'
subplot（2,2,4）
plot（w/pi,angle（h））;
PhaseSpectrum'
Phase,radians'
%Program3_2
%Generatethefiltercoefficients
h1=ones（1,5）/5;
h2=ones（1,14）/14;
%Computethefrequencyresponses
[H1,w]=freqz（h1,1,256）;
[H2,w]=freqz（h2,1,256）;
%Computeandplotthemagnituderesponses
m1=abs（H1）;
m2=abs（H2）;
plot（w/pi,m1,'
w/pi,m2,'
xlabel（'
M=5'
M=14'
%Computeandplotthephaseresponses
ph1=angle（H1）*180/pi;
ph2=angle（H2）*180/pi;
plot（w/pi,ph1,w/pi,ph2）;
Phase,degrees'
%Program3_3
%Setupthefiltercoefficients
b=[-6.7619513.456335-6.76195];
%Setinitialconditionstozerovalues
zi=[00];
%Generatethetwosinusoidalsequences
99;
x1=cos（0.1*n）;
x2=cos（0.4*n）;
%Generatethefilteroutputsequence
y=filter（b,1,x1+x2,zi）;
%Plottheinputandtheoutputsequences
plot（n,y,'
n,x2,'
n,x1,'
g-.'
axis（[0100-1.24]）;
x2[n]'
x1[n]'
%Program4_1
%4-thOrderAnalogButterworthLowpassFilterDesign
formatlong
%Determinezerosandpoles
[z,p,k]=buttap（4）;
Polesareat'
disp（p）;
%Determinetransferfunctioncoefficients
[pz,pp]=zp2tf（z,p,k）;
%Printcoefficientsindescendingpowersofs
Numeratorpolynomial'
disp（pz）
Denominatorpolynomial'
disp（real（pp））
omega=[0:
0.01:
5];
%Computeandplotfrequencyresponse
h=freqs（pz,pp,omega）;
plot（omega,20*log10（abs（h）））;
Normalizedfrequency'
Gain,dB'
%Program4_2
%ProgramtoDesignButterworthLowpassFilter
%Typeinthefilterorderandpassbandedgefrequency
Typeinfilterorder='
Wn=input（'
3-dBcutoffangularfrequency='
%Determinethetransferfunction
[num,den]=butter（N,Wn,'
s'
%Computeandplotthefrequencyresponse
200:
12000*pi];
h=freqs（num,den,omega）;
plot（omega/（2*pi）,20*log10（abs（h）））;
Frequency,Hz'
%Program4_3
%ProgramtoDesignType1ChebyshevLowpassFilter
%Readinthefilterorder,passbandedgefrequency
%andpassbandrippleindB
Order='
Fp=input（'
PassbandedgefrequencyinHz='
Rp=input（'
PassbandrippleindB='
%Determinethecoefficientsofthetransferfunction
[num,den]=cheby1（N,Rp,2*pi*Fp,'
%Program4_4
%ProgramtoDesignEllipticLowpassFilter
%Readinthefilterorder,passbandedgefrequency,
%passbandrippleindBandminimumstopband
%attenuationindB
Rs=input（'
MinimumstopbandattenuationindB='
[num,den]=ellip（N,Rp,Rs,2*pi*Fp,'
functiony=circonv（x1,x2）
%Developsasequenceyobtainedbythecircular
%convolutionoftwoequal-lengthsequencesx1andx2
L1=length（x1）;
L2=length（x2）;
ifL1~=L2,error（'
Sequencesofunequallength'
）,end
y=zeros（1,L1）;
x2tr=[x2
（1）x2（L2:
-1:
2）];
fork=1:
L1,
sh=circshift（x2tr'
k-1）'
h=x1.*sh;
disp（sh）;
y（k）=sum（h）;
end
function[Y]=haar_1D（X）
%ComputestheHaartransformoftheinputvectorX
%ThelengthofXmustbeapower-of-2
%RecursivelybuildstheHaarmatrixH
v=log2（length（X））-1;
H=[11;
1-1];
form=1:
v,
A=[kron（H,[11]）;
2^（m/2）.*kron（eye（2^m）,[1-1]）];
H=A;
Y=H*double（X（:
））;
%Program5_1
%IllustrationofDFTComputation
%ReadinthelengthNofsequenceandthedesired
%lengthMoftheDFT
Typeinthelengthofthesequence='
TypeinthelengthoftheDFT='
%Generatethelength-Ntime-domainsequence
u=[ones（1,N）];
%ComputeitsM-pointDFT
U=fft（u,M）;
%Plotthetime-domainsequenceanditsDFT
t=0:
N-1;
stem（t,u）
Originaltime-domainsequence'
k=0:
M-1;
stem（k,abs（U））
MagnitudeoftheDFTsamples'
Frequencyindexk'
stem（k,angle（U））
PhaseoftheDFTsamples'
Phase'
%Program5_2
%IllustrationofIDFTComputation
%ReadinthelengthKoftheDFTandthedesired
%lengthNoftheIDFT
TypeinthelengthoftheIDFT='
%Generatethelength-KDFTsequence
K-1;
V=k/K;
%ComputeitsN-pointIDFT
v=ifft（V,N）;
%PlottheDFTanditsIDFT
stem（k,V）
OriginalDFTsamples'
stem（n,real（v））
Realpartofthetime-domainsamples'
stem（n,imag（v））
Imaginarypartofthetime-domainsamples'
%Program5_3
%NumericalComputationofFouriertransformUsingDFT
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