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Title: Blind separation of convolutive mixtures of cyclostationary sources using an extended natural gradient method
Authors: Wang, Wenwu
Jafari, Maria G.
Sanei, Saeid
Chambers, Jonathon
Issue Date: 2003
Publisher: © IEEE
Citation: WANG, W. ... et al., 2003. Blind separation of convolutive mixtures of cyclostationary sources using an extended natural gradient method. IN: Proceedings of 2003 7th International Symposium on Signal Processing and Its Applications (ISSPA 2003), Paris, France, 1-4 July, Vol. 2, pp. 93-96.
Abstract: An on-line adaptive blind source separation algorithm for the separation of convolutive mixtures of cyclostationary source signals is proposed. The algorithm is derived by applying natural gradient iterative learning to the novel cost function which is defined according to the wide sense cyclostationarity of signals. The efficiency of the algorithm is supported by simulations, which show that the proposed algorithm has improved performance for the separation of convolved cyclostationary signals in terms of convergence speed and waveform similarity measurement, as compared to the conventional natural gradient algorithm for convolutive mixtures.
Description: This is a conference paper [© IEEE]. It is also available from: http://ieeexplore.ieee.org/. 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/ISSPA.2003.1224823
URI: https://dspace.lboro.ac.uk/2134/5913
ISBN: 0-7803-7946-2
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

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