A Nonlinear Prediction Approach to the Blind Separation of Convolutive Mixtures

Autor: 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
Jazyk: angličtina
Rok vydání: 2007
Předmět:
Zdroj: EURASIP Journal on Advances in Signal Processing, Vol 2007 (2007)
Druh dokumentu: article
ISSN: 1687-6172
1687-6180
DOI: 10.1155/2007/43860
Popis: 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.
Databáze: Directory of Open Access Journals
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