A Variable Step Size Adaptive Algorithm With Simple Parameter Selection

Author(s)

Tiglea, Daniel G. ; Candido, Renato ; Silva, Magno T. M.

• Document type: Journal article
• Source: IEEE SIGNAL PROCESSING LETTERS; v. 29, p. 5-pg., 2022-01-01.

Abstract

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. (AU)

• FAPESP's process: 21/02063-6 - Adaptive filtering and machine learning: applications in diffusion networks, soft sensors and classification of cardiac arrhythmias
• Grantee: Magno Teófilo Madeira da Silva
• Support Opportunities: Regular Research Grants