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Identification of linear discrete-time stochastic system using covariance information

  • Control And Estimation
  • Conference paper
  • First Online:
System Modelling and Optimization

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 113))

  • 165 Accesses

Abstract

This paper presents the new identification procedure of the discrete-time stochastic model in linear time-variant system. The model to be identified has the random input with the white Gaussian property. The variance of the white Gaussian input and the autocovariance function of the signal are assumed to be known. The linear time-variant system is identified by these covariance information.

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References

  1. Ljung, L. and T. Söderström (1983). Theory and practice of recursive identification. MIT Press.

    Google Scholar 

  2. Mehra, R. (1971). On-line identification of linear dynamic systems with applications to Kalman filtering, IEEE Trans. Autom. Contr., vol. AC-16, No.1, pp.12–21.

    Google Scholar 

  3. Nakamori, S. and A. Hataji (1981). New prediction algorithms by covariance information based on innovation theory, Automatica, vol. 17, No.2, pp.379–386.

    Google Scholar 

  4. Sage, A. and J. Melsa (1971). Estimation theory with applications to communications and control. McGraw-Hill.

    Google Scholar 

  5. Nakamori, S. (1983). New design of linear discrete-time predictor using covariance information suitable for predictions of air pollution levels, Proc. of the Fourth International Symposium on the Use of Computers for Environmental Engineering Related to Buildings, pp.246–249.

    Google Scholar 

  6. Kalman, R. and R. Bucy (1961). New results in linear filtering and prediction theory, ASME, J. Basic Eng., vol.83D, pp.95–108.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Technics, Faculty of Education, Kagoshima University, 20-6, 1, 890, Kourimoto, Japan

    Seiichi Nakamori

  2. Department of Applied Mathematics and Physics, Faculty of Engineering, Kyoto University, 606, Kyoto, Japan

    Hidekatsu Tokumaru

Authors
  1. Seiichi Nakamori
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  2. Hidekatsu Tokumaru
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Editor information

Masao Iri Keiji Yajima

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© 1988 International Federation for Information Processing

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Nakamori, S., Tokumaru, H. (1988). Identification of linear discrete-time stochastic system using covariance information. In: Iri, M., Yajima, K. (eds) System Modelling and Optimization. Lecture Notes in Control and Information Sciences, vol 113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0042779

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  • DOI: https://doi.org/10.1007/BFb0042779

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19238-1

  • Online ISBN: 978-3-540-39164-7

  • eBook Packages: Springer Book Archive

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