clear
clc
fs=1000;%采樣頻率
N=1000;%數(shù)據(jù)點(diǎn)數(shù)
n=0:N-1;
t=n/fs;%時(shí)間序列
%構(gòu)造仿真信號(hào)
x=[sin（40*pi*t）+cos（10*pi*t）]+0.8*cos（15*pi*t+pi/3）;
s=x+10*randn（1length（x））
figure;
?subplot（221）;
?plot（tx）;
?xlabel（‘樣本序號(hào)?n‘）;
?ylabel（‘幅值?A‘）;
?title（‘z原始信號(hào)‘）;
?????????????%采用默認(rèn)閾值，用wdencmp函數(shù)進(jìn)行消噪處理
??????[thrsorhkeepappcrit]=ddencmp（‘den‘‘wp‘s）;
??????
????%用全局閾值選項(xiàng)進(jìn)行消噪處理
?????[ctreedperf0perfl2]=wpdencmp（ssorh3‘db2‘critthrkeepapp）;
?????subplot（222）;
?????plot（c）;
?????xlabel（‘樣本序號(hào)?n‘）;
?????ylabel（‘幅值?A‘）;
?????title（‘默認(rèn)閾值消噪信號(hào)‘）;

????%根據(jù)前面的消噪效果，調(diào)節(jié)閾值大小進(jìn)行消噪
?????thr=15;
?????[c1treedperf0perfl2]=wpdencmp（ssorh3‘db2‘critthrkeepapp）;
?????subplot（223）;
?????plot（c1）;
?????xlabel（‘樣本序號(hào)?n‘）;
?????ylabel（‘幅值?A‘）;
?????title（‘調(diào)節(jié)閾值后的消噪信號(hào)‘）;
%?得到Haar小波的提升方案
lshaar