Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/55773
Type: Artigo de periódico
Title: Blind extraction of chaotic sources from mixtures with stochastic signals based on recurrence quantification analysis
Author: Soriano, DC
Suyama, R
Attux, R
Abstract: This work aims to present a new method to perform blind extraction of chaotic deterministic sources mixed with stochastic signals. This technique employs the recurrence quantification analysis (RQA), a tool commonly used to study dynamical systems, to obtain the separating system that recovers the deterministic source. The method is applied to invertible and underdetermined mixture models considering different stochastic sources and different RQA measures. A brief discussion about the influence of recurrence plot parameters on the robustness of the proposal is also provided and illustrated by a set of representative simulations. (C) 2011 Elsevier Inc. All rights reserved.
Subject: Chaotic signals
Blind extraction
Blind source separation
Recurrence quantification analysis
Country: EUA
Editor: Academic Press Inc Elsevier Science
Rights: fechado
Identifier DOI: 10.1016/j.dsp.2010.12.003
Date Issue: 2011
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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