NDLI: Geometrical Structures of FIR Manifold and Multichannel Blind Deconvolution

Content Provider	Springer Nature Link
Author	Zhang, L. Q. Cichocki, A. Amari, S.
Copyright Year	2002
Abstract	In this paper we study geometrical structures of the manifold of Finite Impulse Response (FIR) filters, and develop a natural gradient learning algorithm for blind deconvolution. First, A Lie group structure is introduced to the FIR manifold and the Riemannian metric is then derived by using the isometric property of the Lie group. The natural gradient on the FIR manifold is obtained by introducing a nonholonomic transformation. The Kullback-Leibler divergence is introduced as the measure of mutual independence of the output signals of the demixing model and a feasible cost function is derived for blind deconvolution. An efficient learning algorithm is presented based on the natural gradient approach and its stability analysis is also provided. Finally, we give computer simulations to demonstrate the performance and effectiveness of the proposed natural gradient algorithm.
Starting Page	31
Ending Page	44
Page Count	14
File Format	PDF
ISSN	09225773
Journal	Journal of Signal Processing Systems
Volume Number	31
Issue Number	1
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2002-05-01
Publisher Place	Boston
Access Restriction	Subscribed
Subject Keyword	Signal, Image and Speech Processing Circuits and Systems Electrical Engineering Image Processing and Computer Vision Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Information Systems Electrical and Electronic Engineering

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