A Variable Step Size Adaptive Algorithm with Simple Parameter Selection
Daniel Gilio Tiglea, Renato Candido, Magno T. M. Silva. A Variable Step Size Adaptive Algorithm with Simple Parameter Selection. IEEE Signal Processing Letters, v. 29, pp.1774-1778, 2022.
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.
Variable step size, normalized least mean squares, adaptive filtering, steady-state analysis.