Please use this identifier to cite or link to this item: https://doi.org/10.1049/ip-vis:19941425
Title: Variable-step-size LMS algorithm: new developments and experiments
Authors: Farhang-Boroujeny, B. 
Issue Date: Oct-1994
Source: Farhang-Boroujeny, B. (1994-10). Variable-step-size LMS algorithm: new developments and experiments. IEE Proceedings: Vision, Image and Signal Processing 141 (5) : 311-317. ScholarBank@NUS Repository. https://doi.org/10.1049/ip-vis:19941425
Abstract: The variable-step-size least-mean-square (VSLMS) algorithm is explored and adopted for tracking of time-varying environments. Two implementations of the VSLMS algorithm are proposed. The emphasis is on the implementations with different step sizes at various taps of the adaptive filter. General analysis of the VSLMS algorithm appears to be somewhat involved. However, for one implementation a limited analysis of the algorithm is found possible. For this implementation it is shown that, when the input samples to the adaptive filter are zero-mean. Gaussian and uncorrelated with one another, the VSLMS algorithm can adapt itself to select the optimum set of step sizes which results in the best-tracking performance. Simulation experiments with the VSLMS algorithm show that, under fairly mild conditions, both of the proposed implementations adapt toward the optimum step sizes.
Source Title: IEE Proceedings: Vision, Image and Signal Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/62923
ISSN: 1350245X
DOI: 10.1049/ip-vis:19941425
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