Title :
Orthogonal polynomial-based nonlinear adaptive filters
Author :
Jenkins, W.K. ; Therrien, C.W. ; Li, X.
Author_Institution :
Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA
Abstract :
For certain types of signals, such as white Gaussian signals, the Volterra series can be fully represented by orthogonal polynomials. With an orthogonal polynomial representation, all the nonlinear terms become statistically orthogonal with respect to each other. This allows less computationally complex adaptive algorithms to be developed for adaptive Volterra filters based on the orthogonal polynomial structure.
Keywords :
AWGN; Volterra series; adaptive filters; nonlinear filters; polynomials; signal representation; Volterra series; adaptive Volterra filters; adaptive algorithms; nonlinear adaptive filters; nonlinear terms; orthogonal polynomials; signal representation; statistically orthogonal terms; white Gaussian signals; Adaptive algorithm; Adaptive filters; Convergence; Instruments; Kernel; Lattices; Least squares approximation; Nonlinear systems; Polynomials; Signal generators;
Conference_Titel :
Signals, Systems and Computers, 2001. Conference Record of the Thirty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-7147-X
DOI :
10.1109/ACSSC.2001.987002