资源大小： 486KB
发布时间： 2012-11-14
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资源简介：

Recently Non-negative Matrix Factorization (NMF) hasbecome increasingly popular for feature extraction in com-puter vision and pattern recognition. NMF seeks for twonon-negative matrices whose product can best approximatethe original matrix. The non-negativity constraints lead tosparse, parts-based representations which can be more ro-bust than non-sparse, global features. To obtain more ac-curate control over the sparseness, in this paper, we pro-pose a novel method called Non-negative Local Co


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