Estimating the mixing matrix in Sparse Component Analysis (SCA) based on partial k-dimensional subspace clustering
نویسندگان
چکیده
منابع مشابه
K-Subspace clustering and its application in sparse component analysis
The K-subspace clustering algorithm is established for sparse component analysis and overcome the difficulty that conventional SCA algorithms can not overcome. The conventional SCA algorithm can only perform single dominant SCA, can not perform multiple dominant SCA, but the proposed SCA algorithm based on K-subspace clustering can overcome this difficulty.
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ورودعنوان ژورنال:
- Neurocomputing
دوره 71 شماره
صفحات -
تاریخ انتشار 2008