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Type: Artigo de evento
Title: Source Separation Of Baseband Signals In Post-nonlinear Mixtures
Author: Duarte L.T.
Jutten C.
Rivet B.
Suyama R.
Attux R.
Romano J.M.T.
Abstract: Usually, source separation in Post-Nonlinear (PNL) models is achieved via one-stage methods, i.e. the two parts (linear and nonlinear) of a PNL model are dealt with at the same time. However, recent works have shown that the development of two-stage techniques may simplify the problem. Indeed, if the nonlinear stage can be compensated separately, then, in a second moment, one can make use of the well-established source separation algorithms for the linear case. Motivated by that, we propose in this work a novel two-stage PNL method relying on the assumption that the sources are bandlimited signals. In the development of our method, special care is taken in order to make it as robust as possible to noise. Simulation results attest the effectiveness of the proposal. © 2009 IEEE.
Rights: fechado
Identifier DOI: 10.1109/MLSP.2009.5306214
Date Issue: 2009
Appears in Collections:Unicamp - Artigos e Outros Documentos

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