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Title: Normalised natural gradient algorithm for the separation of cyclostationary sources
Authors: Jafari, Maria G.
Chambers, Jonathon
Keywords: Adaptive filters
Adaptive signal processing
Convergence of numerical methods
Gradient methods
Learning (artificial intelligence)
Source separation
Issue Date: 2003
Publisher: © IEEE
Citation: JAFARI, M.G. and CHAMBERS, J., 2003. Normalised natural gradient algorithm for the separation of cyclostationary sources. IN: IEEE International Conference on Acoustics, Speech, and Signal Processing, Volume 5, pp. V - 301-304
Abstract: A normalised natural gradient algorithm (NGA) for the separation of cyclostationary source signals is proposed in this paper. It improves the convergence properties of the cyclostationary natural gradient algorithm (CSNGA) by employing a gradient adaptive learning rate whose value changes in response to some change in the filter parameters. Experimental results demonstrate the improved behaviour of the approach.
Description: This is a conference paper [© IEEE]. It is also available from: http://ieeexplore.ieee.org/servlet/opac?punumber=8535. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
URI: https://dspace.lboro.ac.uk/2134/5756
ISBN: 0780376633
ISSN: 1520-6149
Appears in Collections:Conference Papers and Contributions (Electronic, Electrical and Systems Engineering)

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