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An LMS style variable tap-length algorithm for structure adaptation

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journal contribution
posted on 30.06.2017, 15:59 by Yu GongYu Gong, Colin F. Cowan
Searching for the optimum tap-length that best balances the complexity and steady-state performance of an adaptive filter has attracted attention recently. Among existing algorithms that can be found in the literature, two of which, namely the segmented filter (SF) and gradient descent (GD) algorithms, are of particular interest as they can search for the optimum tap-length quickly. In this paper, at first, we carefully compare the SF and GD algorithms and show that the two algorithms are equivalent in performance under some constraints, but each has advantages/disadvantages relative to the other. Then, we propose an improved variable tap-length algorithm using the concept of the pseudo fractional tap-length (FT). Updating the tap-length with instantaneous errors in a style similar to that used in the stochastic gradient [or least mean squares (LMS)] algorithm, the proposed FT algorithm not only retains the advantages from both the SF and the GD algorithms but also has significantly less complexity than existing algorithms. Both performance analysis and numerical simulations are given to verify the new proposed algorithm.

Funding

This work was supported by the UK Engineering and Physical Sciences Research Council under Grant GR/S00217/01.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Signal Processing

Volume

53

Issue

7

Pages

2400 - 2407

Citation

GONG, Y. and COWAN, C.F., 2005. An LMS style variable tap-length algorithm for structure adaptation. IEEE Transactions on Signal Processing, 53 (7), pp. 2400-2407.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publication date

2005

Notes

(c) 2005 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

ISSN

1053-587X

eISSN

1941-0476

Language

en