Abstract
Identification of Hammerstein stochastic dynamic systems is investigated. For this problem, the nonlinearities of the system must be taken into account. The solution is derived by recurrent gradient identification algorithms based on the Newton–Raphson and least-squares methods. Convergence is demonstrated, convergence rate is estimated, and parameter estimation accuracy is derived. The procedure is shown to be effective in practice.
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Bolkvadze, G.R. Identification of Hammerstein Nonlinear Stochastic Systems. Automation and Remote Control 63, 601–612 (2002). https://doi.org/10.1023/A:1015178131501
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DOI: https://doi.org/10.1023/A:1015178131501