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Filtering based recursive least squares algorithm for Hammerstein FIR-MA systems. (English) Zbl 1281.93102

Summary: We consider the parameter estimation problem for Hammerstein finite impulse response (FIR) systems. An estimated noise transfer function is used to filter the input-output data of the Hammerstein system. By combining the key-term separation principle and the filtering theory, a recursive least squares algorithm and a filtering-based recursive least squares algorithm are presented. The proposed filtering-based recursive least squares algorithm can estimate the noise and system models. The given examples confirm that the proposed algorithm can generate more accurate parameter estimates and has a higher computational efficiency than the recursive least squares algorithm.

MSC:

93E11 Filtering in stochastic control theory
93E24 Least squares and related methods for stochastic control systems
93E10 Estimation and detection in stochastic control theory
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