A novel data filtering based multi-innovation stochastic gradient algorithm for Hammerstein nonlinear systems |
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Affiliation: | 1. College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China;2. College of Information Engineering, Shenyang university of Chemical Technology, Shenyang, Liaoning Province, 110142 China |
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Abstract: | The identification of nonlinear systems is a hot topic in the identification fields. In this paper, a data filtering based multi-innovation stochastic gradient algorithm is derived for Hammerstein nonlinear controlled autoregressive moving average systems by adopting the key-term separation principle and the data filtering technique. The proposed algorithm provides a reference to improve the identification accuracy of the nonlinear systems with colored noise. The simulation results show that the new algorithm can more effectively estimate the parameters of the Hammerstein nonlinear systems than the multi-innovation stochastic gradient algorithm. |
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Keywords: | Multi-innovation identification Nonlinear system Key-term separation principle Data filtering technique |
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