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Maximum likelihood stochastic gradient estimation for Hammerstein systems with colored noise based on the key term separation technique. (English) Zbl 1236.93150

Summary: We consider the identification problems of Hammerstein finite impulse response moving average (FIR-MA) systems using the maximum likelihood principle and stochastic gradient method based on the key term separation technique. In order to improve the convergence rate, a maximum likelihood multi-innovation stochastic gradient algorithm is presented. The simulation results show that the proposed algorithms can effectively estimate the parameters of the Hammerstein FIR-MA systems.

MSC:

93E12 Identification in stochastic control theory
93E10 Estimation and detection in stochastic control theory
62F10 Point estimation
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