A variable parameter efficient μ-law improved proportionate affine projection algorithm

Author

Xia, Xiao ; Sun, Songlin ; Jing, Xiaojun ; Huang, Hai

Author_Institution

Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2011

fDate

15-17 Sept. 2011

Firstpage

577

Lastpage

581

Abstract

The proportionate affine projection algorithm (APA) was developed for echo cancellation. To further improve the convergence rate and tracking ability, in this paper, a variable parameter μ of the μ-law compression is applied to a recently μ-law “memory”-improved proportionate APA (MMIPAPA). In proposed algorithm, the parameter μ is not constant, but time varying and adaptive. Compared with MMIPAPA, simulation results show that the proposed algorithm, termed the adaptive μ-law “memory”-improved proportionate APA (AMMIPAPA), achieves better convergence performance and owns better tracking ability.

Keywords

affine transforms; echo suppression; μ-law compression; μ-law memory; convergence rate; echo cancellation; proportionate affine projection algorithm; tracking ability; variable parameter efficient μ-law; Adaptive filters; Convergence; Echo cancellers; Projection algorithms; Signal processing algorithms; Adaptive filtering; echo cancellation; proportionate affine projection algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-61284-203-5

Type

conf

DOI

10.1109/CCIS.2011.6045135

Filename

6045135