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Blind deconvolution of timely correlated sources by gradient descent search

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EN
Abstrakty
EN
In multichannel blind decon volution (MB D) the goal is to calculate possibly scaled and delayed estimates of source signals from their convoluted mixtures, using approximate knowledge of the source characteristics oniy. Nearly all of the solutions to MBD proposed so far require from source signals to be pairwise statistically independent and to be timely not correlated. In practice, this can only be satisfied by specific synthetic signals. In this paper we describe how to modify gradient-based iterative algorithms in order to perform the MBD task on timely correlated sources. Implementation issues are discussed and specific tests on synthetic and real 2-D images are documented.
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autor
  • Warsaw University of Technology Institute of Control and Computation Engineering ul. Nowowiejska 15-19, PL - 00-665 Warsaw POLAND, W.Kasprzak@ia.pw.edu.pl
Bibliografia
  • [1] Amari S.. Douglas S.C.. Cichocki A., Yang H.Y.: Novel on-line adaptive learning algorithms for blind deconvolution using the natural gradient approach. IEEE Signal Proc. Workshop on Signal Processing Advances in Wireless Communications. April 1997. Paris, 107 112.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0001-0039
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