Title :
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
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;
Conference_Titel :
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Banff, Alta.
Print_ISBN :
0-8186-8005-9
DOI :
10.1109/HOST.1997.613499
