Multilayer nonnegative matrix factorisation

Authors:

3 August 2006

journal article
Published by Institution of Engineering and Technology (IET) in Electronics Letters

Vol. 42 (16) , 947-948
DOI:10.1049/el:20060983

Abstract

A multilayer approach to nonnegative matrix factorisation algorithms is proposed. It considerably improves their performance; especially if a problem is ill-conditioned, or data are badly scaled, and projected gradient algorithms are used. This is fully confirmed by extensive simulations with diverse types of data in application to blind source separation.

Keywords

MULTILAYER APPROACH
BLIND SOURCE SEPARATION
NONNEGATIVE MATRIX FACTORISATION ALGORITHMS

This publication has 3 references indexed in Scilit:

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Learning the parts of objects by non-negative matrix factorization
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