Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4977616 | Signal Processing | 2017 | 31 Pages |
Abstract
This paper introduces a new gain distribution policy for proportionate normalized least-mean-square (PNLMS)-type algorithms. In the proposed approach, gains assigned to the coefficients that have achieved the vicinity of their optimal values are transferred to other coefficients. To estimate such a vicinity, a metric based on the variation rate of the adaptive filter coefficient magnitude is devised, which is used as a way for assessing the individual-coefficient convergence. Then, the proposed approach is applied to the PNLMS, improved PNLMS (IPNLMS), and individual-activation-factor PNLMS (IAF-PNLMS), leading to enhanced versions of these algorithms. Simulation results show that the proposed approach (and the corresponding enhanced algorithms) performs well for different operating scenarios.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Fábio Luis Perez, Eduardo Vinicius Kuhn, Francisco das Chagas de Souza, Rui Seara,