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Blind extraction of chaotic sources from mixtures with stochastic signals based on recurrence quantification analysis

Authors :
Soriano, Diogo C.
Suyama, Ricardo
Attux, Romis
Source :
Digital Signal Processing. May2011, Vol. 21 Issue 3, p417-426. 10p.
Publication Year :
2011

Abstract

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. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
10512004
Volume :
21
Issue :
3
Database :
Academic Search Index
Journal :
Digital Signal Processing
Publication Type :
Periodical
Accession number :
59915257
Full Text :
https://doi.org/10.1016/j.dsp.2010.12.003