Time series decomposition | MATLAB realizes visualization of signal decomposition components based on wavelet decomposition

Time series decomposition | MATLAB realizes visualization of signal decomposition components based on wavelet decomposition

List of effects

basic introduction

Component visualization based on wavelet decomposition, a MATLAB programming program used to decompose signals into sub-signals of different scales and frequencies. By convolving the wavelet function with the original signal, we can obtain a set of sub-signals of the low-frequency part and the high-frequency part. The low-frequency part represents the general trend or smooth component of the signal, while the high-frequency part represents the details or rapidly changing components in the signal.
It can be used by reading from an Excel table and directly replacing the data without requiring major changes to the program. There are detailed comments in the program to facilitate understanding of program operation.

programming

• Complete source code and data acquisition method: private message reply MATLAB realizes visualization of signal decomposition components based on wavelet decomposition .

%%  清空环境变量
warning off             % 关闭报警信息
close all               % 关闭开启的图窗
clear                   % 清空变量
clc                     % 清空命令行

cosD = pdist(meas,'cosine');
clustTreeCos = linkage(cosD,'average');
cophenet(clustTreeCos,cosD)

ans =

    0.9360
[h,nodes] = dendrogram(clustTreeCos,0);
h_gca = gca;
h_gca.TickDir = 'out';
h_gca.TickLength = [.002 0];
h_gca.XTickLabel = [];
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版权声明：本文为CSDN博主「机器学习之心」的原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/kjm13182345320/article/details/119920826



figure
hidx = cluster(clustTreeCos,'criterion','distance','cutoff',.006);
for i = 1:5
    clust = find(hidx==i);
    plot3(meas(clust,1),meas(clust,2),meas(clust,3),ptsymb{
    
    i});
    hold on
end
hold off
xlabel('Sepal Length');
ylabel('Sepal Width');
zlabel('Petal Length');
view(-137,10);
grid on

————————————————
版权声明：本文为CSDN博主「机器学习之心」的原创文章，遵循CC 4.0 BY-SA版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/kjm13182345320/article/details/119920826

References

[1] https://blog.csdn.net/kjm13182345320/article/details/129215161
[2] https://blog.csdn.net/kjm13182345320/article/details/128105718