Statistical Identification of Kernels of Discrete Nonlinear Systems
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 approximation to Gaussian noise provides a computational efficiency of this method, especially for high order kernels. Orthogonal functionals and consistent estimations for Wiener kernels in the frequency domains are derived for this class of noise input. A basis of the proposed computational procedure for practical identification is the fast Fourier transform (FFT) algorithm which is used both for a generating of system stimuluses and for an analysis of system reactions.
Persistent identifier
http://hdl.handle.net/11012/58357Document type
Peer reviewedDocument version
Final PDFSource
Radioengineering. 1997, vol. 6, č. 1, s. 16-18. ISSN 1210-2512http://www.radioeng.cz/fulltexts/1997/97_01_03.pdf
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- 1997/1 [5]