An Adaptive Diffusion Augmented CLMS Algorithm for Distributed Filtering of Noncircular Complex Signals

Author

Yili Xia ; Mandic, Danilo P. ; Sayed, Ali H.

Author_Institution

Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK

Volume

18

Issue

11

fYear

2011

Firstpage

659

Lastpage

662

Abstract

An adaptive diffusion augmented complex least mean square (D-ACLMS) algorithm for collaborative processing of the generality of complex signals over distributed networks is proposed. The algorithm enables the estimation of both second order circular (proper) and noncircular (improper) signals within a unified framework of augmented complex statistics. The analysis shows that the performance advantage of the widely linear D-ACLMS over the strictly linear D-CLMS increases with the degree of noncircularity while maintaining similar performance for proper data. Simulations on both synthetic benchmark and real world noncircular data support the approach.

Keywords

adaptive filters; least mean squares methods; statistics; adaptive diffusion; augmented CLMS algorithm; augmented complex statistics; collaborative processing; complex least mean square; distributed filtering; distributed networks; noncircular complex signals; noncircular signals; real world noncircular data support; second order circular signals; Adaptation models; Algorithm design and analysis; Estimation; Network topology; Peer to peer computing; Signal processing algorithms; Vectors; Adaptive diffusion; distributed estimation; noncircular complex signals; widely linear modelling;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2011.2168390

Filename

6020746