A Nonlinear Prediction Approach to the Blind Separation of Convolutive Mixtures

A Nonlinear Prediction Approach to the Blind Separation of Convolutive Mixtures

We propose a method for source separation of convolutive mixture based on nonlinear prediction-error filters. This approach converts the original problem into an instantaneous mixture problem, which can be solved by any of the several existing methods in the literature. We employ fuzzy filters to im...

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Bibliographic Details
Main Authors: João Marcos Travassos Romano, Fernando José Von Zuben, Charles Casimiro Cavalcante, Romis Ribeiro de Faissol Attux, Leandro Elias Paiva Rangel, Rafael Ferrari, Leonardo Tomazeli Duarte, Ricardo Suyama
Format: Article
Language:English
Published: SpringerOpen 2007-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://dx.doi.org/10.1155/2007/43860
Description
Summary:We propose a method for source separation of convolutive mixture based on nonlinear prediction-error filters. This approach converts the original problem into an instantaneous mixture problem, which can be solved by any of the several existing methods in the literature. We employ fuzzy filters to implement the prediction-error filter, and the efficacy of the proposed method is illustrated by some examples.
ISSN:1687-6172
1687-6180

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