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基于奇异值分解的特征提取方法,采用标准模糊C均值聚类(fuzzy C means clustering, FC

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发表于 2024-1-17 02:06:16 | 显示全部楼层 |阅读模式
基于奇异值分解的特征提取方法,采用标准模糊C均值聚类(fuzzy C means clustering, FCM)进行故障识别

文件列表:
EMI.m
FCMClus2t.m
KFCMClust.m
MI.m
Main.fig
Main.m
VMD.m
VMD_sin_center_f.m
VMD_singular.m
VMD_test.m
VMD_test_original.m
VMD_winddata.m
cluster_SAME_con_VMD_casedata.asv
cluster_SAME_con_VMD_casedata.m
cluster_var1_con_VMD_casedata.asv
cluster_var1_con_VMD_casedata.m
cluster_var2_con_VMD_casedata.asv
cluster_var2_con_VMD_casedata.m
cluster_var3_con_VMD_casedata.asv
cluster_var3_con_VMD_casedata.m
distfcm.m
emd_vmd_con.asv
emd_vmd_con.m
fuzzydist.m
hua_baoluo.m
hua_fft1.asv
hua_fft1.m
hua_xihua.m
imssdata.mat
initfcm.m
labview_data.m
matlab.dat
matlab1.dat
muting.m
plot_imf.m
stepfcm11.m
stepfcm_hxm.m
test.m
test2.m

运行例图:
01.jpg


基于奇异值分解的特征提取方法,采用标准模糊C均值聚类(fuzzy C means clustering, FC.zip (382.07 KB, 下载次数: 0, 售价: 30 积分)


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