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Article title RECURSIVE ESTIMATION BILINEAR DYNAMICAL SYSTEMS WITH ERRORS-IN-VARIABLES
Authors D.V. Ivanov, O.V. Uskov
Section SECTION V. HIGH-EFFICIENCY COMPUTING ALGORITHMS
Month, Year 06, 2012 @en
Index UDC 519 .254.1
DOI
Abstract It is well known that the method of least squares gives biased estimates of parameters for dynamic systems when the observed input-output data are corrupted with noise. Recursive algorithm based on stochastic approximation is proposed for identification single-input-single-output (SISO) bilinear dynamic systems with errors-in-variables. The estimates are proved to be convergent to the true values with probability one, the resulting estimates of parameters under constraints that do not require knowledge of density. The proposed algorithm was realized in Matlab and compared with the recursive least-squares method and the recursive method extended instrumental variables. The results of a simulated example indicate that the proposed algorithm provides good estimates.

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Keywords Recursive estimation; stochastic approximation; errors-in-variables model; bilinear systems; least square method.
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