A Variable Step Size Adaptive Algorithm With Simple Parameter Selection

We propose a normalized least mean squares algorithm with variable step size. Unlike other solutions, it has low computational cost, only three parameters that are simple to choose, and its steady-state performance can be easily predicted. Simulations show a competitive performance in comparison wit...

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Bibliographic Details
Published in:IEEE signal processing letters Vol. 29; pp. 1774 - 1778
Main Authors: Tiglea, Daniel G., Candido, Renato, Silva, Magno T. M.
Format: Journal Article
Language:English
Published: New York IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive algorithms
Adaptive filtering
Adaptive filters
Convergence
Filtering algorithms
Least mean squares
Least mean squares algorithm
normalized least mean squares
Parameters
Prediction algorithms
Signal processing algorithms
Steady-state
steady-state analysis
Transient analysis
variable step size
ISSN:1070-9908, 1558-2361
Online Access:Get full text
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Summary:We propose a normalized least mean squares algorithm with variable step size. Unlike other solutions, it has low computational cost, only three parameters that are simple to choose, and its steady-state performance can be easily predicted. Simulations show a competitive performance in comparison with other solutions, and validate our theoretical analysis.
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2022.3195662