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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Vydáno v:IEEE signal processing letters Ročník 29; s. 1774 - 1778
Hlavní autoři: Tiglea, Daniel G., Candido, Renato, Silva, Magno T. M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
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
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2022.3195662