A class of nonlinear adaptive filters

Author

Palmieri, Francesco ; Boncelet, C.G., Jr.

Author_Institution

Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA

fYear

1988

fDate

11-14 Apr 1988

Firstpage

1483

Abstract

A generalized framework for the description of a large class of nonlinear filters is introduced. This framework includes nonrecursive linear filters (FIR), order statistic filters (OSF or L-filters), Ll -filters, Volterra filters, and ZNL-LTI filters. The Ll-filters have been proposed to generalize and combine FIR and OSF filters. LMS and RLS algorithms are extended to such a class, and a simulation of an adaptive line enhancer using an L-filter is presented

Keywords

digital filters; filtering and prediction theory; FIR filters; L-filters; LMS filters; Ll-filters; RLS algorithms; Volterra filters; ZNL-LTI filters; adaptive filters; adaptive line enhancer; digital filters; nonlinear filters; nonrecursive linear filters; order statistic filters; Adaptive filters; Finite impulse response filter; Least squares approximation; Nonlinear filters; Random variables; Resonance light scattering; Statistics; Storms; Systems engineering and theory; Vectors;

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.1988.196883

Filename

196883

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3002889