代码搜索：IP软核
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www.eeworm.com/read/456377/7350191
h ip6_misc.h
/*
* Copyright (c) 1993, 1994, 1997
* The Regents of the University of California. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are
www.eeworm.com/read/456354/7351281
m ip_06_07.m
% MATLAB script for Illustrative Problem 7, Chapter 6.
echo on
N=31;
T=1;
alpha=1/4;
n=-(N-1)/2:(N-1)/2; % The indices for g_T
% The expression for g_T is obtained next
for i=1:length(n),
g_T(i)=0
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m ip_06_06.m
% MATLAB script for Illustrative Problem 6, Chapter 6.
echo on
N=52;
noise_var=0.25;
sigma=sqrt(noise_var); % standard deviation of the noise
for i=1:N, % generate data sequence
if (rand
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m ip_06_09.m
% MATLAB script for Illustrative Problem 9, Chapter 6.
echo on
d=[1 1 1 0 1 0 0 1 0 0 0 1];
p(1)=0;
for i=1:length(d)
p(i+1)=rem(p(i)+d(i),2);
echo off ;
end
echo on ;
a=2.*p-1;
b(1)=0;
dd(1)=0;
f
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m ip_06_11.m
% MATLAB script for Illustrative Problem 11, Chapter 6.
echo on
T=1;
for n=-2:2,
for k=-2:2,
temp=0;
for i=-2:2, temp=temp+(1/(1+(n-i)^2))*(1/(1+(k-i)^2)); end;
X(k+3,n+3)=temp;
echo
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m ip_06_04.m
% MATLAB script for Illustrative Problem 4, Chapter 6.
echo on
Length=101;
Fs=10000;
W=2000;
Ts=1/Fs;
n=-(Length-1)/2:(Length-1)/2;
t=Ts*n;
h=2*W*sinc(2*W*t);
% The rectangular windowed versio
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m ip_06_02.m
% MATLAB script for Illustrative Problem 2, Chapter 6.
echo on
T=1;
delta_f=1/(100*T);
f=-5/T:delta_f:5/T;
Sv=2*(cos(pi*f*T).*sinc(f*T)).^2;
% plotting command follows
plot(f,Sv);
www.eeworm.com/read/456354/7351289
m ip_06_03.m
% MATLAB script for Illustrative Problem 3, Chapter 6.
echo on
f_cutoff=2000; % the desired cut-off frequency
f_stopband=2500; % the actual stopband frequency
fs=10000; % the sampling frequenc
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m ip_06_10.m
% MATLAB script for Illustrative Problem 10, Chapter 6.
echo on
T=1;
Fs=2/T;
Ts=1/Fs;
c_opt=[-2.2 4.9 -3 4.9 -2.2];
t=-5*T:T/2:5*T;
x=1./(1+((2/T)*t).^2); % sampled pulse
equalized_x=filte
www.eeworm.com/read/456354/7351291
m ip_06_05.m
% MATLAB script for Illustrative Problem 5, Chapter 6.
echo on
p=0.99;
N=1000;
d=5;
% The filter is described by the vectors A and B below...
A=[1 -2*p p^2];
B=(1-p)^2;
for i=1:N,
[white_noise_seq1