典型文献
Structured sparsity assisted online convolution sparse coding and its application on weak signature detection
文献摘要：
Due to the strong background noise and the acquisition system noise,the useful characteristics are often difficult to be detected.To solve this problem,sparse coding captures a con-cise representation of the high-level features in the signal using the underlying structure of the sig-nal.Recently,an Online Convolutional Sparse Coding(OCSC)denoising algorithm has been proposed.However,it does not consider the structural characteristics of the signal,the sparsity of each iteration is not enough.Therefore,a threshold shrinkage algorithm considering neighbor-hood sparsity is proposed,and a training strategy from loose to tight is developed to further improve the denoising performance of the algorithm,called Variable Threshold Neighborhood Online Convolution Sparse Coding(VTNOCSC).By embedding the structural sparse threshold shrinkage operator into the process of solving the sparse coefficient and gradually approaching the optimal noise separation point in the training,the signal denoising performance of the algorithm is greatly improved.VTNOCSC is used to process the actual bearing fault signal,the noise inter-ference is successfully reduced and the interest features are more evident.Compared with other existing methods,VTNOCSC has better denoising performance.
文献关键词：
中图分类号：
作者姓名：
Huijie MA;Shunming LI;Jiantao LU;Zongzhen ZHANG;Siqi GONG
作者机构：
College of Energy&Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
文献出处：
引用格式：
[1]Huijie MA;Shunming LI;Jiantao LU;Zongzhen ZHANG;Siqi GONG-.Structured sparsity assisted online convolution sparse coding and its application on weak signature detection)[J].中国航空学报（英文版）,2022(01):266-276
A类：
OCSC,VTNOCSC
B类：
Structured,sparsity,assisted,online,convolution,sparse,coding,its,application,weak,signature,detection,Due,strong,background,noise,acquisition,system,useful,characteristics,often,difficult,detected,To,solve,this,problem,captures,cise,representation,high,level,features,signal,using,underlying,structure,Recently,Online,Convolutional,Sparse,Coding,denoising,algorithm,has,been,proposed,However,does,not,structural,each,iteration,enough,Therefore,threshold,shrinkage,considering,neighbor,training,strategy,from,loose,tight,developed,further,performance,called,Variable,Threshold,Neighborhood,By,embedding,operator,into,process,solving,coefficient,gradually,approaching,optimal,separation,point,greatly,improved,used,actual,bearing,fault,ference,successfully,reduced,interest,more,evident,Compared,other,existing,methods,better
AB值：
0.557368
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