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Título:
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Parametric Approach to Blind Deconvolution of Nonlinear Channels
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Autor/a:
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Solé-Casals, Jordi; Jutten, Christian; Taleb, Anisse
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Otros autores:
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Universitat de Vic. Escola Politècnica Superior; Universitat de Vic. Grup de Recerca en Tecnologies Digitals; European Symposium on Artificial Neural Networks, ESANN (8ª: 2000 : Bèlgica) |
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Notas:
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A parametric procedure for the blind inversion of nonlinear channels is
proposed, based on a recent method of blind source separation in nonlinear
mixtures. Experiments show that the proposed algorithms perform
efficiently, even in the presence of hard distortion. The method, based on
the minimization of the output mutual information, needs the knowledge of
log-derivative of input distribution (the so-called score function). Each
algorithm consists of three adaptive blocks: one devoted to adaptive
estimation of the score function, and two other blocks estimating the
inverses of the linear and nonlinear parts of the channel, (quasi-)optimally
adapted using the estimated score functions. This paper is mainly
concerned by the nonlinear part, for which we propose two parametric
models, the first based on a polynomial model and the second on a neural
network, while [14, 15] proposed non-parametric approaches. |
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Materia(s):
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-Tractament del senyal |
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Derechos:
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(c) Elsevier, 2002
Tots els drets reservats
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Tipo de documento:
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Artículo
info:eu-repo/acceptedVersion |
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Editor:
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Elsevier
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Compartir:
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