Parallel adaptation for enhanced RLS tracking

Author

Peters, S. Douglas ; Antoniou, Andreas

Author_Institution

Defence Res. Establ. Atlantic, Dartmouth, NS, Canada

Volume

iii

fYear

1994

fDate

19-22 Apr 1994

Abstract

A new variable forgetting factor RLS adaptive filter is introduced. This algorithm, based on an accurate new measure of RLS performance in a random walk scenario, attempts to achieve the optimal RLS steady-state misadjustment under the assumption that the Wiener filter coefficients vary according to that nonstationarity. Simulations demonstrate that the proposed method is effective in other nonstationary environments and outperforms existing fixed and variable forgetting factor schemes

Keywords

Wiener filters; adaptive filters; least squares approximations; random processes; recursive filters; tracking filters; RLS adaptive filter; Wiener filter coefficients; enhanced RLS tracking; nonstationary environments; optimal RLS steady-state misadjustment; parallel adaptation; random walk scenario; simulations; variable forgetting factor; Accuracy; Adaptive filters; Additive noise; Markov processes; Performance analysis; Predictive models; Resonance light scattering; Steady-state; Transversal filters; Wiener filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on

Conference_Location

Adelaide, SA

ISSN

1520-6149

Print_ISBN

0-7803-1775-0

Type

conf

DOI

10.1109/ICASSP.1994.390087

Filename

390087