Title :
On reduced-complexity approximations of quadratic filters
Author :
Marsi, Stefano ; Sicuranza, Giovanni L.
Author_Institution :
Dipartimento di Elettrotecnica Elettronica ed Inf., Trieste Univ., Italy
Abstract :
Among the various mathematical representations of nonlinear systems, a popular description is given by means of the discrete-time Volterra series. In this paper we first briefly review the relevant nonlinear system identification techniques, with reference in particular to nonlinear systems with lengthy memory. In such cases, a parallel-cascade structure has been proved to be very effective since it is able to provide an arbitrarily close approximation, in the mean square error (MSE) sense, for a broad class of systems to be modelled. The parallel-cascade structure is indeed an exact representation for a quadratic filter, obtained by means of a matrix decomposition technique: we recall such a technique and then we show how it is possible to apply it for the adaptive identification of quadratic systems with large time delays
Keywords :
delays; filtering and prediction theory; identification; matrix algebra; series (mathematics); adaptive identification; discrete-time Volterra series; large time delays; lengthy memory; mathematical representations; matrix decomposition; mean square error; nonlinear system identification; nonlinear systems; parallel-cascade structure; quadratic filters; quadratic systems; reduced-complexity approximations; Adaptive filters; Delay effects; Electronic mail; Finite impulse response filter; IIR filters; Kernel; Linear systems; Matrix decomposition; Mean square error methods; Nonlinear systems; Polynomials; Stability;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342414
