New paper: 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 with other solutions, and validate our theoretical analysis.

The PDF file can be obtained in this page.


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