小波阈值语音消噪clc;clear;fs=wavread('G:\c12345.wav');y=fs(1000:12000);N=length(y);figure(1);subplot(111);plot(y);ylabel('幅值 A');title('原始信号');s=awgn(y,20,'measured');%加入高斯白噪声figure(2);plot(s);ylabel('幅值 A');titl
来源:学生作业帮助网 编辑:作业帮 时间:2024/07/18 10:16:21
![小波阈值语音消噪clc;clear;fs=wavread('G:\c12345.wav');y=fs(1000:12000);N=length(y);figure(1);subplot(111);plot(y);ylabel('幅值 A');title('原始信号');s=awgn(y,20,'measured');%加入高斯白噪声figure(2);plot(s);ylabel('幅值 A');titl](/uploads/image/z/8800933-13-3.jpg?t=%E5%B0%8F%E6%B3%A2%E9%98%88%E5%80%BC%E8%AF%AD%E9%9F%B3%E6%B6%88%E5%99%AAclc%3Bclear%3Bfs%3Dwavread%28%27G%3A%5Cc12345.wav%27%29%3By%3Dfs%281000%3A12000%29%3BN%3Dlength%28y%29%3Bfigure%281%29%3Bsubplot%28111%29%3Bplot%28y%29%3Bylabel%28%27%E5%B9%85%E5%80%BC+A%27%29%3Btitle%28%27%E5%8E%9F%E5%A7%8B%E4%BF%A1%E5%8F%B7%27%29%3Bs%3Dawgn%28y%2C20%2C%27measured%27%29%3B%25%E5%8A%A0%E5%85%A5%E9%AB%98%E6%96%AF%E7%99%BD%E5%99%AA%E5%A3%B0figure%282%29%3Bplot%28s%29%3Bylabel%28%27%E5%B9%85%E5%80%BC+A%27%29%3Btitl)
小波阈值语音消噪clc;clear;fs=wavread('G:\c12345.wav');y=fs(1000:12000);N=length(y);figure(1);subplot(111);plot(y);ylabel('幅值 A');title('原始信号');s=awgn(y,20,'measured');%加入高斯白噪声figure(2);plot(s);ylabel('幅值 A');titl
小波阈值语音消噪
clc;
clear;
fs=wavread('G:\c12345.wav');
y=fs(1000:12000);
N=length(y);
figure(1);
subplot(111);
plot(y);
ylabel('幅值 A');
title('原始信号');
s=awgn(y,20,'measured');%加入高斯白噪声
figure(2);
plot(s);
ylabel('幅值 A');
title('加噪信号');
wname='db3';%选db3小波基
lev=5;%5层分解
[c,l]=wavedec(s,lev,wname);
a5=appcoef(c,l,wname,lev);
d5=detcoef(c,l,5);
d4=detcoef(c,l,4);
d3=detcoef(c,l,3);
d2=detcoef(c,l,2);
d1=detcoef(c,l,1);
cD=[d1 d2 d3 d4 d5];%运行到这里出错.提示d1,d2,d3,d4,d5维数不同不兼容.
小波阈值语音消噪clc;clear;fs=wavread('G:\c12345.wav');y=fs(1000:12000);N=length(y);figure(1);subplot(111);plot(y);ylabel('幅值 A');title('原始信号');s=awgn(y,20,'measured');%加入高斯白噪声figure(2);plot(s);ylabel('幅值 A');titl
因为的确d1~d5的元素个数不同,离散小波变换一层比一层少一半数据量,即元素个数少一半.通常信号处理中,在变换完成后要进行重构,是一种插值处理.变换得到的小波系数毫无用处,有时得到的是稀疏矩阵,甚至不是实数,无法分析和成图.因此,必须利用小波系数进行重构(即小波逆变换,可使用wrcoef函数)才是您所想要得到处理结果.