Blind Source Separation of Overdetermined Linear-Quadratic Mixtures View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010

AUTHORS

Leonardo T. Duarte , Ricardo Suyama , Romis Attux , Yannick Deville , João M. T. Romano , Christian Jutten

ABSTRACT

This work deals with the problem of source separation in overdetermined linear-quadratic (LQ) models. Although the mixing model in this situation can be inverted by linear structures, we show that some simple independent component analysis (ICA) strategies that are often employed in the linear case cannot be used with the studied model. Motivated by this fact, we consider the more complex yet more robust ICA framework based on the minimization of the mutual information. Special attention is given to the development of a solution that be as robust as possible to suboptimal convergences. This is achieved by defining a method composed of a global optimization step followed by a local search procedure. Simulations confirm the effectiveness of the proposal. More... »

PAGES

263-270

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-15995-4_33

DOI

http://dx.doi.org/10.1007/978-3-642-15995-4_33

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018321060


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