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Título:
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Blind channel deconvolution of real world signals using source separation techniques
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Autor/a:
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Solé-Casals, Jordi; Monte-Moreno, Enric
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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; International Conference on Non-Linear Speech Processing NOLISP (2005 : Barcelona) |
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Notas:
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In this paper we present a method for blind deconvolution of linear
channels based on source separation techniques, for real word signals. This
technique applied to blind deconvolution problems is based in exploiting not
the spatial independence between signals but the temporal independence between
samples of the signal. Our objective is to minimize the mutual information
between samples of the output in order to retrieve the original signal. In
order to make use of use this idea the input signal must be a non-Gaussian i.i.d.
signal. Because most real world signals do not have this i.i.d. nature, we will
need to preprocess the original signal before the transmission into the channel.
Likewise we should assure that the transmitted signal has non-Gaussian statistics
in order to achieve the correct function of the algorithm. The strategy used
for this preprocessing will be presented in this paper. If the receiver has the inverse
of the preprocess, the original signal can be reconstructed without the
convolutive distortion. |
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Materia(s):
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-Tractament del senyal |
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Derechos:
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(c) Springer, 2005
Tots els drets reservats
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Tipo de documento:
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Objeto de conferencia |
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Editor:
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Springer
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