Title :
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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on
Conference_Location :
New York, NY
DOI :
10.1109/ICASSP.1988.196883
