Fast RLS with parallel computations

Author

Djigan, Victor I.

Author_Institution

R&D Center of Microelectronics, ELVEES, Moscow, Russia

fYear

2005

fDate

23-24 June 2005

Firstpage

42

Lastpage

45

Abstract

The paper presents parallel forms of the sliding window fast RLS algorithms with the regularization of adaptive filter correlation matrix. The new algorithms are mathematically identical to the appropriate algorithms with sequential computations, but can be implemented by means of parallel processors. The algorithms are based on the using of the generalized matrix inversion lemma. They can be used for the processing of non-stationary signals.

Keywords

adaptive filters; adaptive signal processing; filtering theory; least squares approximations; parallel processing; recursive filters; adaptive filter correlation matrix; generalized matrix inversion lemma; nonstationary signal; parallel computation; parallel processor; sliding window fast RLS algorithm; Adaptive filters; Adaptive signal processing; Concurrent computing; Filtering algorithms; Least squares approximation; Linear matrix inequalities; Neural networks; Resonance light scattering; Signal processing; Signal processing algorithms; Adaptive filtering; RLS; fast RLS; parallel computations;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Technologies: Circuits and Systems for 4G Mobile Wireless Communications, 2005. ETW '05. 2005 IEEE 7th CAS Symposium on

Print_ISBN

5-7422-0895-2

Type

conf

DOI

10.1109/EMRTW.2005.195676

Filename

1529543