Title :
MMD-ARMA approximation to the Volterra series expansion
Author :
Kafka, Veit S. ; Appel, Ulrich
Author_Institution :
Univ. der Bundeswehr Munchen, Germany
Abstract :
Nonlinear filtering based on the Volterra series expansion is a powerful universal tool in signal processing. Due to the problem of increased complexity for higher orders and filter lengths, approximations up to third order nonlinearities using linear FIR-filters and multipliers have been developed earlier called multimemory decomposition (MMD). In our paper we go a step further in this approach using ARMA-filters instead which leads to a reduction in the number of coefficients to about 50% for similar system functions. The good performance of this new approach is demonstrated by means of a processor designed for identification of nonlinear loudspeaker distortions.
Keywords :
Volterra series; approximation theory; audio signal processing; autoregressive moving average processes; computational complexity; identification; loudspeakers; nonlinear filters; transfer functions; ARMA-filters; MMD-ARMA approximation; Volterra series expansion; complexity; filter lengths; linear FIR-filters; multi memory decomposition; nonlinear filtering; nonlinear loudspeaker distortions; signal processing; system functions; third order nonlinearities; Filtering; Loudspeakers; Matrix decomposition; Nonlinear distortion; Nonlinear filters; Nonlinear systems; Process design; Signal processing; Transfer functions; Vectors;
Conference_Titel :
Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-5148-7
DOI :
10.1109/ACSSC.1998.750867