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A Variable Step Size Adaptive Algorithm With Simple Parameter Selection
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DOI：10.1109/LSP.2022.3195662.png)
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摘要
En 中文
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.
Keyword:
Steady-state
Signal processing algorithms
Convergence
Adaptive filters
Filtering algorithms
Prediction algorithms
Transient analysis
Adaptive filtering
normalized least mean squares
steady-state analysis
variable step size
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
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