代码:

function y = circonvt(x1,x2,N)
%% N-point Circular convolution between x1 and x2: (time domain)
%% ------------------------------------------------------------------
%% [y] = circonvt(x1,x2,N)
%% y = output sequence containning the circular convolution
%% x1 = input sequence of length N1 <= N
%% x2 = input sequence of length N2 <= N
%%
%% N = size of circular buffer
%% Method: y(n) = sum( x1(m)*x2((n-m) mod N) )
%% Check for length of x1 if length(x1) > N
error('N must be >= the length of x1 !')
end
%% Check for length of x2 if length(x2) > N
error('N must be >= the length of x2 !')
end x1 = [x1 zeros(1,N-length(x1))];
x2 = [x2 zeros(1,N-length(x2))]; m = [0:1:N-1]; x2 = x2(mod_1(-m, N)+1); H = zeros(N,N);
for n = 1:1:N
H(n,:) = cirshftt(x2,n-1,N);
end
y = x1*conj(H'); % x1---row vector
% H
% y = H*x1'; % x1---column vector

  主程序:

%% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
%% Output Info about this m-file
fprintf('\n***********************************************************\n');
fprintf(' <DSP using MATLAB> Problem 5.24 \n\n'); banner();
%% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ % -------------------------------------------------------------------
%
% -------------------------------------------------------------------
N = 4;
n1 = [0:3];
x1 = [1, 2, 2]; x2 = [1, 2, 3, 4]; y1 = circonvt(x1, x2, N)

  运行结果:

代码:

function [C] = circulnt(x, N)
%% Circulant Matrix from an N-point sequence
%% ------------------------------------------------------------------
%% [C] = circulnt(x, N)
%% C = Circulant Matrix of size NxN
%% x = sequence of length <= N
%%
%% N = size of circulant matrix
if length(x) > N
error('N must be >= the length of x !')
end x = [x zeros(1, N-length(x))]; for i = 1 : N
c(i) = x(i);
end m = [0:1:N-1]; x_fold = x(mod_1(-m, N)+1);
r = x_fold; C = toeplitz(c,r);

  

function y = circonvt_v3(x1,x2,N)
%% N-point Circular convolution between x1 and x2: (time domain)
%% ------------------------------------------------------------------
%% [y] = circonvt(x1,x2,N)
%% y = output sequence containning the circular convolution
%% x1 = input sequence of length N1 <= N
%% x2 = input sequence of length N2 <= N
%%
%% N = size of circular buffer
%% Method: y(n) = sum( x1(m)*x2((n-m) mod N) )
%% Check for length of x1 if length(x1) > N
error('N must be >= the length of x1 !')
end
%% Check for length of x2
if length(x2) > N
error('N must be >= the length of x2 !')
end x1 = [x1 zeros(1,N-length(x1))];
x2 = [x2 zeros(1,N-length(x2))]; C = circulnt(x2, N); % m = [0:1:N-1]; x2 = x2(mod_1(-m, N)+1); H = zeros(N,N);
% for n = 1:1:N
% H(n,:) = cirshftt(x2,n-1,N);
% end
% y = x1*conj(H'); % x1---row vector y = C*x1'; % x1---column vector

  

%% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
%% Output Info about this m-file
fprintf('\n***********************************************************\n');
fprintf(' <DSP using MATLAB> Problem 5.25 \n\n'); banner();
%% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ % -------------------------------------------------------------------
%
% -------------------------------------------------------------------
N = 4;
n1 = [0:3];
x1 = [1, 2, 2]; x2 = [1, 2, 3, 4]; %C = circulnt(x2, 4); y1 = circonvt_v3(x1, x2, N)

  运行结果:

代码:

function x3 = circonvf(x1, x2, N)
%% N-point Circular convolution between x1 and x2: (frequency domain)
%% ------------------------------------------------------------------
%% [x3] = circonvf(x1,x2,N)
%% x3 = output sequence containning the circular convolution
%% x1 = input sequence of length N1 <= N
%% x2 = input sequence of length N2 <= N
%%
%% N = size of circular buffer
%% Method: x3(n) = IDFT[X1(k)X2(k)] %% Check for length of x1
if length(x1) > N
error('N must be >= the length of x1 !')
end
%% Check for length of x2
if length(x2) > N
error('N must be >= the length of x2 !')
end x1 = [x1 zeros(1,N-length(x1))];
x2 = [x2 zeros(1,N-length(x2))]; X1k_DFT = dft(x1, N);
X2k_DFT = dft(x2, N); x3 = real(idft( X1k_DFT.* X2k_DFT, N));

  

%% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
%% Output Info about this m-file
fprintf('\n***********************************************************\n');
fprintf(' <DSP using MATLAB> Problem 5.26 \n\n'); banner();
%% +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ % -------------------------------------------------------------------
%
% -------------------------------------------------------------------
N = 4;
n1 = [0:3];
x1 = [4,3,2,1];
%x1 = [1,2,2]; n2 = [0:3];
x2 = [1, 2, 3, 4]; %C = circulnt(x2, 4); y1 = circonvf(x1, x2, N)

  运行结果:

《DSP using MATLAB》Problem 5.24-5.25-5.26的更多相关文章

  1. 《DSP using MATLAB》Problem 7.24

    又到清明时节,…… 注意:带阻滤波器不能用第2类线性相位滤波器实现,我们采用第1类,长度为基数,选M=61 代码: %% +++++++++++++++++++++++++++++++++++++++ ...

  2. 《DSP using MATLAB》Problem 6.24

    代码: %% ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ %% Output In ...

  3. 《DSP using MATLAB》Problem 4.24

    Y(z)部分分式展开, 零状态响应部分分式展开, 零输入状态部分分式展开,

  4. 《DSP using MATLAB》Problem 6.15

    代码: %% ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ %% Output In ...

  5. 《DSP using MATLAB》Problem 6.8

    代码: %% ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ %% Output In ...

  6. 《DSP using MATLAB》Problem 4.15

    只会做前两个, 代码: %% ---------------------------------------------------------------------------- %% Outpu ...

  7. 《DSP using MATLAB》Problem 2.16

    先由脉冲响应序列h(n)得到差分方程系数,过程如下: 代码: %% ------------------------------------------------------------------ ...

  8. 《DSP using MATLAB》 Problem 2.3

    本题主要是显示周期序列的. 1.代码: %% ------------------------------------------------------------------------ %% O ...

  9. 《DSP using MATLAB》Problem 7.29

    代码: %% ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ %% Output In ...

随机推荐

  1. spring bean 的生命周期

    感谢博友,内容源于博友的文章 http://www.cnblogs.com/zrtqsk/p/3735273.html 通过了解spring的bean 的生命周期 ,再结合jdk的注解,继承sprin ...

  2. svg 学习笔记

    http://git.oschina.net/heboliufengjie/demo/tree/master/svg?dir=1&filepath=svg&oid=3a44203972 ...

  3. 深入研究sqlalchemy连接池

    简介: 相对于最新的MySQL5.6,MariaDB在性能.功能.管理.NoSQL扩展方面包含了更丰富的特性.比如微秒的支持.线程池.子查询优化.组提交.进度报告等. 本文就主要探索MariaDB当中 ...

  4. 使用perfect进行服务端开发

    最近闲来无事,研究了下基于perfect的swift后端开发.根据大神的博客进行了简单的配置,加深下印象也算是和各位分享一下. 参考博客:http://www.cnblogs.com/ludashi ...

  5. substr、substring和slice的区别

    substr(start,[length])表示从start位置开始取length个字符串:substring(start,end)表示从start,到end之间的字符串,包括start位置的字符但是 ...

  6. ps基础学习笔记一

    图像?表示分为位图方式和矢量图方式 位图是像素点组成,一副图像所含像素越多,图像的效果就越好 矢量图是基于一定数学方式描述,适合表示色彩较少,一色块为主,曲线简单的图像,文件小ps一般用来处理位图,c ...

  7. oracle截取字段中的部分字符串

    使用Oracle中Instr()和substr()函数: 在Oracle中可以使用instr函数对某个字符串进行判断,判断其是否含有指定的字符. 其语法为: instr(sourceString,de ...

  8. Zookeeper与Paxos

    初识Zookeeper zookeeper为分布式应用提供了高效且可靠的分布式协调服务,提供了诸如统一命名服务.配置管理和分布式锁等分布式的基础服务. 在解决分布式数据一致性方面,zk没有直接采用Pa ...

  9. python自学第6天,文件修改,字符编码

    文件的修改: 一般是把旧文件的内容改了,在写入到新的文件中去. file_old=open("test","r",encoding="utf-8&qu ...

  10. 莫烦tensorflow(3)-Variable

    import tensorflow as tf state = tf.Variable(0,name='counter') one = tf.constant(1) new_value = tf.ad ...