Fast estimation of Wiener kernels of nonlinear systems in the frequency domain

Author

Shcherbakov, Miichael A.

Author_Institution

IVS, State Tech. Univ. of Penza, Penza, Russia

fYear

1997

fDate

21-23 Jul 1997

Firstpage

117

Lastpage

121

Abstract

A method for identification of discrete nonlinear systems in terms of the Volterra-Wiener series is presented. It is shown that use of a special composite-frequency input signal as an approximation to Gaussian noise provides the computational efficiency of this method especially for high order kernels. Orthogonal functionals and consistent estimates for Wiener kernels in the frequency domain are derived for this class of noise input. The basis of the proposed computational procedure for practical identification is the fast Fourier transform (FFT) algorithm which is used both for generation of actions and for analysis of system reactions

Keywords

Gaussian noise; Volterra series; discrete systems; estimation theory; fast Fourier transforms; frequency-domain analysis; function approximation; identification; nonlinear systems; spectral analysis; stochastic processes; Gaussian noise; Volterra-Wiener series; Wiener kernels; composite-frequency input signal; computational efficiency; computational procedure; discrete nonlinear systems; fast Fourier transform; fast estimation; frequency domain; high order kernels; identification; noise input; nonlinear systems; orthogonal functionals; system reactions; Control system synthesis; Fast Fourier transforms; Frequency domain analysis; Frequency estimation; Gaussian noise; Gaussian processes; Kernel; Noise generators; Nonlinear systems; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on

Conference_Location

Banff, Alta.

Print_ISBN

0-8186-8005-9

Type

conf

DOI

10.1109/HOST.1997.613499

Filename

613499