EENG 851: Signal Processing II

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EENG 851 Signal Processing II

• Exercise Solutions
• Ex 2 Due

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Exercise 2 Solution
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Exercise 2 Solution
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Exercise Set 2
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Exercise Set 2
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Exercise Set 2
EENG 851 Spring 08 Exercise 2-b Sample
Autocorrelation of White Noise Saved as
adspex2_2b08.m 2/27/08 N2000 M64
White Noise Signals v1sqrt(12)(
rand(1,N)-0.5) Zero mean uniform

acft(1/4)zeros(1,M-4) 1 0 -4 0 6 0 -4 0 1
zeros(1,M-4) True autocorrelation
Filtering Operation b(1/2)1 0
0 -1 a1 y1filter(b,a,v1)

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Exercise Set 2
Autocovariance
phiy1, lagsy1xcov(y1,M,'unbiased')
fi
gure(1)clf subplot(211),stem(lagsy1,phiy1,'fill')
grid title('Calculated Output AutocorrelationUni
form Input Process') ylabel('Amplitude') axis(-7
0 70 -.1 .6) subplot(212),stem(lagsy1,acft,'fill'
)grid title('Theoretical Output Autocorrelation
Uniform Input Process') xlabel('Sample') ylabel('A
mplitude')
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Exercises Class 2
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Exercise Set 2
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Exercise 2
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Exercise 2
EENG851 Spring 2007 ADSP Exercise 2d
Sample Autocorrelation of White Noise Saved as
adspex2_2d07.m 2/27/07 N2000 M64 a1.7
White Noise Signals v1sqrt
(12)(rand(1,N)-0.5) Zero mean
uniform
Filtering Operation
b0.3 a1 -a1 y1filter(b,a,v1)

True Autocorrelation
Sequence rhs(3/17)(a1).(0M) lhs
(3/7)(a1).(M-11) acftlhs
rhs

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Exercise 2
Autocovariance phiy1,
lagsy1xcov(y1,M,'unbiased')
figure(1)clf subplo
t(211),stem(lagsy1,phiy1)grid title('Calculated
Output AutocorrelationUniform Input
Process') ylabel('Amplitude') axis(-70 70 -.2
.2) subplot(212),stem(lagsy1,acft)grid title('Th
eoretical Output Autocorrelation Uniform Input
Process') xlabel('Sample') ylabel('Amplitude') axi
s(-70 70 -.2 .2)