Title :
Convergence performance of adaptive lattice filters with nonlinear parameter updates
Author :
Kumura, T. ; Liguni, Y. ; Maeda, H.
Author_Institution :
Dept. of Commun. Eng., Osaka Univ., Japan
fDate :
6/1/2000 12:00:00 AM
Abstract :
The convergence properties of adaptive lattice filters with nonlinear parameter updates have been analysed. The theoretical expressions for the convergence rate and the asymptotic error variance of the PARCOR coefficient are derived. Using these expressions, the convergence performance in the absence of impulsive noise is investigated and compared with those of the linear-type and sign-type adaptive lattice filters. Furthermore, the mean parameter variation caused by an impulsive noise and the parameter recovery time are evaluated to comprehensively compare the convergence performances in the presence of impulsive noise
Keywords :
adaptive filters; adaptive signal processing; convergence of numerical methods; correlation methods; error analysis; filtering theory; impulse noise; lattice filters; network parameters; LMS algorithm; PARCOR coefficient; asymptotic error variance; convergence performance; convergence properties; convergence rate; impulsive noise; least mean square algorithm; linear-type adaptive lattice filters; mean parameter variation; nonlinear parameter updates; parameter recovery time; partial correlation; sign-type adaptive lattice filters; transversal filter structure;
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
DOI :
10.1049/ip-vis:20000332
