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Computer Research and Modeling, 2012, Volume 4, Issue 4, Pages 721–733
DOI: https://doi.org/10.20537/2076-7633-2012-4-4-721-733
(Mi crm524)
 

NUMERICAL METHODS AND THE BASIS FOR THEIR APPLICATION

Test-signals forming method for correlation identification of nonlinear systems

D. Yu. Dunyushkin

Dmitrov branch of Dubna International University for Nature, Society, and Man, 23 DZFS str., Dmitrov, Moscow Region, 141800, Russia
References:
Abstract: Тhe new test-signals forming method for correlation identification of a nonlinear system based on Lee–Shetzen cross-correlation approach is developed and tested. Numerical Gauss–Newton algorithm is applied to correct autocorrelation functions of test signals. The achieved test-signals have length less than 40 000 points and allow to measure the 2nd order Wiener kernels with a linear resolution up to 32 points, the 3rd order Wiener kernels with a linear resolution up to 12 points and the 4th order Wiener kernels with a linear resolution up to 8 points.
Keywords: nonlinear dynamic systems, Volterra–Wiener approach, system identification, cross-correlation ap- proach, Lee–Shetzen method, test-signals, white noise.
Received: 12.10.2012
Document Type: Article
UDC: 519.688
Language: Russian
Citation: D. Yu. Dunyushkin, “Test-signals forming method for correlation identification of nonlinear systems”, Computer Research and Modeling, 4:4 (2012), 721–733
Citation in format AMSBIB
\Bibitem{Dun12}
\by D.~Yu.~Dunyushkin
\paper Test-signals forming method for correlation identification of nonlinear systems
\jour Computer Research and Modeling
\yr 2012
\vol 4
\issue 4
\pages 721--733
\mathnet{http://mi.mathnet.ru/crm524}
\crossref{https://doi.org/10.20537/2076-7633-2012-4-4-721-733}
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