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Title: A combined Kalman filter and natural gradient algorithm approach for blind separation of binary distributed sources in time-varying channels
Authors: Jafari, Maria G.
Seah, H.W.
Chambers, Jonathon
Keywords: Kalman filters
Filtering theory
Gradient methods
Learning systems
Mean square error methods
Time-varying channels
Tracking filters
Issue Date: 2001
Publisher: © IEEE
Citation: JAFARI, M.G., SEAH, H.W. and CHAMBERS, J., 2001. A combined Kalman filter and natural gradient algorithm approach for blind separation of binary distributed sources in time-varying channels. IN: IEEE International Conference on Acoustics, Speech and Signal Processing, Salt Lake City, UT, 7-11 May, Volume 5, pp. 2769 - 2772
Abstract: A combined Kalman filter (KF) and natural gradient algorithm (NGA) approach is proposed to address the problem of blind source separation (BSS) in time-varying environments, in particular for binary distributed signals. In situations where the mixing channel is nonstationary, the performance of the NGA is often poor. Typically, in such cases, an adaptive learning rate is used to help the NGA track the changes in the environment. The Kalman filter, on the other hand, is the optimal, minimum mean square error method for tracking certain non-stationarity. Experimental results are presented, and suggest that the combined approach performs significantly better than NGA in the presence of both continuous and abrupt non-stationarities
Description: This is a conference paper [© IEEE]. It is also available from: http://ieeexplore.ieee.org/servlet/opac?punumber=7486. 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
DOI: 10.1109/ICASSP.2001.940220
URI: https://dspace.lboro.ac.uk/2134/5820
ISBN: 0780370414
Appears in Collections:Conference Papers and Contributions (Electronic, Electrical and Systems Engineering)

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