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Type: Artigo de periódico
Title: Blind Compensation of Nonlinear Distortions: Application to Source Separation of Post-Nonlinear Mixtures
Author: Duarte, LT
Suyama, R
Rivet, B
Attux, R
Romano, JMT
Jutten, C
Abstract: In this paper, we address the problem of blind compensation of nonlinear distortions. Our approach relies on the assumption that the input signal is bandlimited. We then make use of the classical result that the output of a nonlinearity has a wider spectrum than the one of the input signal. However, differently from previous works, our approach does not assume knowledge of the input signal bandwidth. The proposal is considered in the development of a two-stage method for blind source separation (BSS) in post-nonlinear (PNL) models. Indeed, once the functions present in the nonlinear stage of a PNL model are compensated, one can apply the well-established linear BSS algorithms to complete the task of separating the sources. Numerical experiments performed in different scenarios attest the viability of the proposal. Moreover, the proposed method is tested in a real situation where the data are acquired by smart chemical sensor arrays.
Subject: Bandlimited signals
blind source separation
nonlinear distortion
post-nonlinear model
smart chemical sensor arrays
Country: EUA
Editor: Ieee-inst Electrical Electronics Engineers Inc
Rights: fechado
Identifier DOI: 10.1109/TSP.2012.2208953
Date Issue: 2012
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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