Regularized nonnegative matrix factorization: Geometrical interpretation and application to spectral unmixing

Regularized nonnegative matrix factorization: Geometrical interpretation and application to spectral unmixing

Nonnegative Matrix Factorization (NMF) is an important tool in data spectral analysis. However, when a mixing matrix or sources are not sufficiently sparse, NMF of an observation matrix is not unique. Many numerical optimization algorithms, which assure fast convergence for specific problems, may easi...

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Bibliographic Details
Main Author: Zdunek Rafał
Format: Article
Language:English
Published: Sciendo 2014-06-01
Series:International Journal of Applied Mathematics and Computer Science
Subjects:
blind source separation
nonnegative matrix factorization
active-set algorithm
regularized NMF
polytope approximation
Online Access:http://www.degruyter.com/view/j/amcs.2014.24.issue-2/amcs-2014-0017/amcs-2014-0017.xml?format=INT

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http://www.degruyter.com/view/j/amcs.2014.24.issue-2/amcs-2014-0017/amcs-2014-0017.xml?format=INT

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