Theorems on Positive Data: On the Uniqueness of NMF

Publication: Research - peer-reviewJournal article – Annual report year: 2008

Documents

DOI

View graph of relations

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.
Original languageEnglish
Article number764206
JournalComputational Intelligence and Neuroscience
Publication date2008
Volume2008
Pages10
ISSN1687-5265
DOIs
StatePublished

Bibliographical note

Copyright © 2008 Hans Laurberg et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

CitationsWeb of Science® Times Cited: No match on DOI
Download as:
Download as PDF
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
Word

ID: 4830183