Timing Decomposition | MATLAB Realizes Visualization of Signal Decomposition Components Based on LMD Local Mean Decomposition

Timing Decomposition | MATLAB Realizes Visualization of Signal Decomposition Components Based on LMD Local Mean Decomposition

Effect list

basic introduction

LMD local mean decomposition can directly replace Excel and run Matlab language including spectrogram and correlation coefficient diagram
1. The algorithm is novel and niche, and few people use it. It includes decomposition diagram, spectrogram, and correlation coefficient diagram. The effect is as shown in the figure. It is suitable as Create❤️~
2. Directly replace the Excel data and use it. Suitable for novices and clear annotations~
3. Comes with test data and run main directly to generate graphs with one click~

programming

• Complete source code and data acquisition method: Reply to MATLAB via private message to realize the visualization of signal decomposition components based on LMD local mean 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