Title :
Identification of FIR Wiener systems with unknown, noninvertible, polynomial nonlinearities
Author :
Lacy, Seth L. ; Bernstein, Dennis S.
Author_Institution :
Dept. of Aerosp. Eng., Michigan Univ., Ann Arbor, MI, USA
Abstract :
Wiener systems consist of a linear dynamic system whose output is measured through a static nonlinearity. In this paper we study the identification of single-input single-output Wiener systems with finite impulse response and polynomial nonlinearities. Our approach is to use multi-index notation to first solve a least squares problem to estimate products of the coefficients of the nonlinearity and the impulse response of the linear system. We then present four methods to extract the coefficients of the nonlinearity and impulse response: direct algebraic solutions, a singular value decomposition, a multi-dimensional singular value decomposition, and a prediction error optimization approach.
Keywords :
FIR filters; least squares approximations; optimisation; singular value decomposition; transient response; FIR Wiener systems; direct algebraic solutions; finite impulse response nonlinearities; impulse response; least squares problem; linear dynamic system; multi-dimensional singular value decomposition; multi-index notation; noninvertible polynomial nonlinearities; prediction error optimization approach; single input single-output Wiener systems; singular value decomposition; static nonlinearity; Finite impulse response filter; Least squares approximation; Linear systems; Linearity; Nonlinear dynamical systems; Nonlinear systems; Optimization methods; Polynomials; Signal generators; Singular value decomposition;
Conference_Titel :
American Control Conference, 2002. Proceedings of the 2002
Print_ISBN :
0-7803-7298-0
DOI :
10.1109/ACC.2002.1023129