Theorems on positive data: on the uniqueness of NMF.
Pagination
764206 - ?
DOI
10.1155/2008/764206
Journal
Comput Intell Neurosci
ISSN
1687-5265
Metadata
Show full item recordAbstract
We investigate the conditions for which nonnegative matrix factorization (NMF) is unique and introduce several theorems which can determine whether the decomposition is in fact unique or not. The theorems are illustrated by several examples showing the use of the theorems and their limitations. We have shown that corruption of a unique NMF matrix by additive noise leads to a noisy estimation of the noise-free unique solution. Finally, we use a stochastic view of NMF to analyze which characterization of the underlying model will result in an NMF with small estimation errors.