Recurrent least square learning for quasi-parallel principal component analysis
نویسندگان
چکیده
The recurrent least squares (RLS) learning approach is proposed for controlling the learning rate in parallel principal subspace analysis (PSA) and in a wide class of principal component analysis (PCA) associated algorithms with a quasi{parallel extraction ability. The purpose is to provide a useful tool for applications where the learning process has to be repeated in an on{line self{adaptive manner. The methods are compared with a sequential PCA method for image compression.
منابع مشابه
Recurrent Least Squares Learning for Quasi{parallel Principal Component Analysis
The recurrent least squares (RLS) learning approach is proposed for controlling the learning rate in parallel principal subspace analysis (PSA) and in a wide class of principal component analysis (PCA) associated algorithms with a quasi{parallel extraction ability. The purpose is to provide a useful tool for applications where the learning process has to be repeated in an on{line self{adaptive ...
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تاریخ انتشار 1996