Go to content
UR Home

Hybridizing sparse component analysis with genetic algorithms for blind source separation

Stadlthanner, K. ; Theis, Fabian J. ; Lang, Elmar ; Puntonet, Carlos G. Oliveira, José Luis , eds.


Nonnegative Matrix Factorization (NMF) has proven to be a useful tool for the analysis of nonnegative multivariate data. However, it is known not to lead to unique results when applied to nonnegative Blind Source Separation (BSS) problems. In this paper we present first results of an extension to the NMF algorithm which solves the BSS problem when the underlying sources are sufficiently sparse. ...


Owner only: item control page
  1. Homepage UR

University Library

Publication Server


Publishing: oa@ur.de

Dissertations: dissertationen@ur.de

Research data: daten@ur.de

Contact persons