Two spatio-temporal decorrelation learning algorithms and their application to multichannel blind deconvolution

Seungjin Choi, Andrzej Cichocki, Shun ichi Amari

Research output: Contribution to journalConference articlepeer-review

12 Citations (Scopus)

Abstract

In this paper we present and compare two different spatio-temporal decorrelation learning algorithms for updating the weights of a linear feedforward network with FIR synapses (MIMO FIR filter). Both standard gradient and the natural gradient are employed to derive the spatio-temporal decorrelation algorithms. These two algorithms are applied to multichannel blind deconvolution task and their performance is compared. The rigorous derivation of algorithms and computer simulation results are presented.

Original languageEnglish
Pages (from-to)1085-1088
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
Publication statusPublished - 1999
Externally publishedYes
EventProceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99) - Phoenix, AZ, USA
Duration: 15 Mar 199919 Mar 1999

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