This paper is concerned with the iteration identification algorithm for Hammerstein model with complex-valued input for the fact that the existing algorithms are not valid for complex input. Based on the stochastic gr...
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ISBN:
(纸本)9781510804166
This paper is concerned with the iteration identification algorithm for Hammerstein model with complex-valued input for the fact that the existing algorithms are not valid for complex input. Based on the stochastic gradient algorithm, the extended stochastic gradient algorithm is proposed by defining new cost function for complex input. The extended hierarchical multi-innovation stochastic gradient algorithm is proposed by introducing multi-innovation identification theory and hierarchical principle to the extended stochastic gradient algorithm. Experimental simulations show that the extended hierarchical multi-innovation stochastic gradient algorithm has better performance than the extended stochastic gradient algorithm at the expense of computational complexity.
The Volterra model can approximate many nonlinear systems,and it is a typical nonlinear *** paper studies the parameter estimation problem of the Volterra *** the Levenberg-Marquardt optimization method and the recurs...
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The Volterra model can approximate many nonlinear systems,and it is a typical nonlinear *** paper studies the parameter estimation problem of the Volterra *** the Levenberg-Marquardt optimization method and the recursive identification method,we propose a Levenberg-Marquardt recursive algorithm and apply it to the identification of the Volterra *** order to verify the feasibility of the above algorithm,the second-order Volterra system is simulated using the Levenberg-Marquardt recursive algorithm and the forgetting factor stochastic gradient algorithm respectively,and then we compare the simulation results of the Volterra system under the two *** simulation results show that the above two algorithms can identify the parameters of the Volterra *** with the forgetting factor stochastic gradient algorithm,the Levenberg-Marquardt recursive algorithm has faster convergence speed and higher convergence *** proves the effectiveness of the Levenberg-Marquardt recursive algorithm.
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