A fast recursive least-squares second order Volterra filter

Author

Mathews, V. John ; Lee, Junghsi

Author_Institution

Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT, USA

fYear

1988

fDate

11-14 Apr 1988

Firstpage

1383

Abstract

A fast, recursive least-squares (RLS) adaptive nonlinear filter is presented. The nonlinearity is modeled using a second-order Volterra-series expansion. The structure makes use of the ideas of fast RLS multichannel filters and has a computational complexity of O(N ³) multiplications. This compares with O(N⁶) multiplications required for direct implementation. Simulation examples in which the filter is employed to identify nonlinear systems using noisy output observations are also presented. Further simplification to the structure through a simplified model is discussed

Keywords

digital filters; filtering and prediction theory; least squares approximations; RLS multichannel filters; adaptive nonlinear filter; computational complexity; fast recursive least-squares; multiplications; noisy output observations; nonlinear systems; nonlinearity; second order Volterra filter; simulation; Adaptive filters; Cities and towns; Computational complexity; Computational modeling; Delay; Least squares approximation; Noise cancellation; Nonlinear filters; Nonlinear systems; Resonance light scattering;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on

Conference_Location

New York, NY

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1988.196855

Filename

196855