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An optimised normalised LMF algorithm for sub-Gaussian noise

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3 Author(s)
M. K. Chan ; Sch. of Electr. & Electron. Eng., Queen's Univ., Belfast, UK ; A. Zerguine ; C. F. N. Cowan

The least mean fourth (LMF) algorithm is known for its fast convergence and lower steady state error, especially under sub-Gaussian noise conditions. Meanwhile, the recent work on the normalised versions of LMF algorithm has further enhanced its stability and performance in both Gaussian and sub-Gaussian noise. For example, the normalised LMF (XE-NLMF) algorithm, recently developed, is normalised by the mixed signal power and error power, and weighted by a fixed mixed-power parameter. Unfortunately, this algorithm depends on the selection of this mixing parameter. To overcome this obstacle, in this work, a time-varying mixed-power parameter technique is introduced to optimise its selection. An enhancement in performance is obtained through the use of this procedure in both the convergence rate and steady-state error.

Published in:

Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on  (Volume:6 )

Date of Conference:

6-10 April 2003