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Properties of the momentum LMS algorithm
Date
1989-10
Author
Tugay, Mehmet Ali
Tanik, Yalçin
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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One of the most recent modifications on Widrow and Hoff's LMS algorithm has been the inclusion of a momentum term into the weight update equation. The resulting algorithm is referred to as “The Momentum LMS (MLMS) algorithm”. This paper revises the basic properties of the MLMS algorithm for stationary inputs. As a result, new bounds, on the parameters of the algorithm, for convergence are found, and it is shown that, under slow convergence conditions, this new algorithm is equivalent to the usual LMS algorithm, but it outperforms the LMS algorithm for fast convergence cases and for inputs containing inpulsive noise components.
Subject Keywords
Control and Systems Engineering
,
Signal Processing
,
Electrical and Electronic Engineering
,
Software
,
Computer Vision and Pattern Recognition
URI
https://hdl.handle.net/11511/51702
Journal
Signal Processing
DOI
https://doi.org/10.1016/0165-1684(89)90044-3
Collections
Department of Electrical and Electronics Engineering, Article
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M. A. Tugay and Y. Tanik, “Properties of the momentum LMS algorithm,”
Signal Processing
, pp. 117–127, 1989, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51702.