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Identification of Objects by the Maximal Information Criterion

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Abstract

The design of predictive input-output models for linear and nonlinear systems with random signals is studied. Definitions are formulated and conditions for identifiability by information criteria are derived. A consistent method of identification of systems by the maximal information criterion is designed. The values of parameters of an object are used for identifying and designing unbiased models.

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Authors and Affiliations

  1. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

    I. S. Durgaryan & F. F. Pashchenko

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  1. I. S. Durgaryan
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  2. F. F. Pashchenko
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Durgaryan, I.S., Pashchenko, F.F. Identification of Objects by the Maximal Information Criterion. Automation and Remote Control 62, 1104–1114 (2001). https://doi.org/10.1023/A:1010209910967

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