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Time-varying signal processing using multi-wavelet basis functions and a modified block least mean square algorithm

Li, Y., Wei, H.L. and Billings, S.A. (2009) Time-varying signal processing using multi-wavelet basis functions and a modified block least mean square algorithm. Research Report. ACSE Research Report no. 998 . Automatic Control and Systems Engineering, University of Sheffield

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Abstract

This paper introduces a novel parametric modeling and identification method for linear time-varying systems using a modified block least mean square (LMS) approach where the time-varying parameters are approximated using multi-wavelet basis functions. This approach can be used to track rapidly or even sharply varying processes and is more suitable for recursive estimation of process parameters by combining wavelet approximation theory with a modified block LMS algorithm. Numerical examples are provided to show the effectiveness of the proposed method for dealing with severely nonstatinoary processes.

Item Type: Monograph (Research Report)
Copyright, Publisher and Additional Information: The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
Keywords: Time variation, Parameter estimation, System identification, B-spline basis function, normalized least mean square (NLMS), modified block least mean square (MBLMS).
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) > ACSE Research Reports
Depositing User: Miss Anthea Tucker
Date Deposited: 16 Oct 2012 10:21
Last Modified: 06 Jun 2014 09:54
Status: Published
Publisher: Automatic Control and Systems Engineering, University of Sheffield
URI: http://eprints.whiterose.ac.uk/id/eprint/74650

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