Proposal of blind source separation methods for convolutive and nonlinear mixtures / Proposta de metodos de separação cega de fontes para misturas convolutivas e não-lineares

AUTOR(ES)
DATA DE PUBLICAÇÃO

2007

RESUMO

The problem of blind source separation (BSS) has attracted the attention of agrowing number of researchers, mostly due to its potential applications in a significant number of different areas. The objective of the present work is to propose new methods to solve the problem of BSS in the cases of convolutive mixtures and nonlinear mixtures. For the first case, we propose a new method based on nonlinear prediction filters. The nonlinear structure is employed to eliminate the convolutive character of the mixture, hence converting the problem into an instantaneous mixture, to which several well established tools may be used to recover the sources. In the context of nonlinear mixtures, we present a new methodology for signal separation in the so-called post-nonlinear mixing models (PNL). In order to avoid convergence to local minima, the proposed method uses an evolutionary algorithm to perform the optimization of the separating system. In addition to that, we employ an entropy estimator based on order-statistics to evaluate the cost function. The effectiveness of both methods is assessed through simulations in different scenarios

ASSUNTO(S)

independent component analysis nonlinear mixtures convolutive mistures teoria da informação digital signal processing processamento de sinais blind source separation information theory adaptive signal processing processamento de sinal adaptativo

ACESSO AO ARTIGO

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