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2001 | 11 | 4 | 977-991

Tytuł artykułu

Recursive identification of Wiener systems

Treść / Zawartość

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
A Wiener system, i.e. a cascade system consisting of a linear dynamic subsystem and a nonlinear memoryless subsystem is identified. The a priori information is nonparametric, i.e. neither the functional form of the nonlinear characteristic nor the order of the dynamic part are known. Both the input signal and the disturbance are Gaussian white random processes. Recursive algorithms to estimate the nonlinear characteristic are proposed and their convergence is shown. Results of numerical simulation are also given. A known algorithm recovering the impulse response of the dynamic part is presented in a recursive form.

Rocznik

Tom

11

Numer

4

Strony

977-991

Opis fizyczny

Daty

wydano
2001
otrzymano
2001-02-16
poprawiono
2001-08-07

Twórcy

  • Institute of Engineering Cybernetics, Wrocław University of Technology, Wybrzeże S. Wyspiańskiego 27, 50-370 Wrocław, Poland,

Bibliografia

  • Ahmad I.P. and Lin N. (1976): Nonparametric sequential estimation of multiple regression function. — Bull. Math. Statist., Vol.17, pp.63–75.
  • Billings S. (1980): Identification of nonlinear systems — A survey. — IEE Proc., Vol.127, pp.272–285.
  • Billings S. and Fakhouri S. (1977): Identification of nonlinear systems using the Wiener model. — Electron. Lett., Vol.13, pp.502–504.
  • Billings S. and Fakhouri S. (1978): Theory of separable processes with applications to the identification of nonlinear systems. — IEE Proc., Vol.125, pp.1051–1058.
  • Brillinger D. (1977): The identification of a particular nonlinear time series system. — Biometrica, Vol.64, pp.509–515.
  • Collomb M. (1977): Quelques proprietés de la méthode du noyau pour l’estimation non paramétrique de la régression en un point fixé. — C. R. Acad. Sc. Paris, Vol.285, pp.289–292 (in French).
  • den Brinker A. (1989): A comparison of results from parameter estimations of impulse responses of the transient visual system. — Biol. Cybern., Vol.61, pp.139–151.
  • Devroye L. and Wagner T. (1980): On the L1-convergence of kernel estimators of regression functions with application in discrimination. — Z. Wahrsch. Verv. Gebiete, Vol.51, pp.15–25.
  • Greblicki W. (1992): Nonparametric identification of Wiener systems. — IEEE Trans. Inf. Theory, Vol.38, pp.1487–1493.
  • Greblicki W. (1997): Nonparametric approach to Wiener system identification. — IEEE Trans. Circuits and Systems I: Fundamental Theory and Applications, Vol.44, pp.538– 545.
  • Greblicki W. and Pawlak M. (1987): Necessary and sufficient consistency conditions for a recursive kernel regression estimate. — J. Multivar. Anal., Vol.23, pp.67–76.
  • Hunter I. and Korenberg M. (1986): The identification of nonlinear biological systems: Wiener and Hammerstein cascade models. — Biol. Cybern., Vol.55, pp.135–144.
  • Kalafatis A., Afirin N., Wang L. and Cluett W. (1995): A new approach to the identification of pH processes based on the Wiener model. — Chem. Eng. Sci., Vol.23, pp.3693–3701.
  • Krzyzak A. and Pawlak M. (1984): Almost everywhere convergence of a recursive regression estimate and classification. — IEEE Trans. Inf. Theory, Vol.30, pp.91–93.
  • Krzyżak A. and Partyka A.M. (1993): On identificcation of block oriented systems by nonparametric techniques. — Int. J. Syst. Sci., Vol.24, pp.1049–1066.
  • Nadaraya E. (1964): On regression estimators. — Theory Prob. Appl., Vol.9, pp.157–159.
  • Watson G. (1964): Smooth regression analysis. — Sankhyā, Ser. A, Vol. 26, pp.359–372.
  • Westwick D. and Kearney R. (1992): A new algorithm for the identification of multiple input Wiener systems. — Biol. Cybern., Vol.68, pp.75–85.
  • Westwick D. and Verhaegen M. (1996): Identifying MIMO Wiener systems using subspace model identification methods. — Signal Process., Vol.52, pp.235–258.
  • Wheeden R. and Zygmund A. (1977): Measure and Integral. — New York: Dekker.
  • Wigren T. (1993): Recursive prediction error identification using the nonlinear Wiener model. — Automatica, Vol.29, pp.1011–1025.

Typ dokumentu

Bibliografia

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