Geometrical structures of FIR manifold and their application to multichannel blind deconvolution

L. Q. Zhang, A. Cichocki, S. Amari

Research output: Contribution to conferencePaperpeer-review

15 Citations (SciVal)

Abstract

In this paper we study geometrical structures on the manifold of FIR filters and their application to multichannel blind deconvolution. First we introduce the Lie group and Riemannian metric to the manifold of FIR filters. Then we derive the natural gradient on the manifold using the isometry of the Riemannian metric. Using the natural gradient, we present a novel learning algorithm for blind deconvolution based on the minimization of mutual information. We also study properties of the learning algorithm, such as equivariance and stability. Simulations are given to illustrate the effectiveness and validity of the proposed algorithm.

Original languageEnglish
Pages303-312
Number of pages10
Publication statusPublished - 1999
Externally publishedYes
EventProceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99) - Madison, WI, USA
Duration: 23 Aug 199925 Aug 1999

Conference

ConferenceProceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99)
CityMadison, WI, USA
Period23/08/9925/08/99

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