Reconstruction of reflectance spectra using robust nonnegative matrix factorization
نویسندگان
چکیده
منابع مشابه
Robust near-separable nonnegative matrix factorization using linear optimization
Nonnegative matrix factorization (NMF) has been shown recently to be tractable under the separability assumption, which amounts for the columns of the input data matrix to belong to the convex cone generated by a small number of columns. Bittorf, Recht, Ré and Tropp (‘Factoring nonnegative matrices with linear programs’, NIPS 2012) proposed a linear programming (LP) model, referred to as HottTo...
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Nonnegative matrix factorization (NMF) has been successfully used in many fields as a low-dimensional representation method. Projective nonnegative matrix factorization (PNMF) is a variant of NMF that was proposed to learn a subspace for feature extraction. However, both original NMF and PNMF are sensitive to noise and are unsuitable for feature extraction if data is grossly corrupted. In order...
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ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2006
ISSN: 1053-587X
DOI: 10.1109/tsp.2006.879282