This paper discusses the identification problems of Hammerstein controlled autoregressive autoregressive (CARAR) systems using the maximum likelihood principle and newton optimization method. A newtonrecursive algori...
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This paper discusses the identification problems of Hammerstein controlled autoregressive autoregressive (CARAR) systems using the maximum likelihood principle and newton optimization method. A newton recursive algorithm and a newton iterative algorithm using the maximum likelihood principle are presented. The simulation results show that the proposed algorithms can effectively estimate the parameters of the Hammerstein CARAR systems.
A novel newton recursive algorithm is proposed for an optimum design of arrayed waveguide gratings, which is different from the traditional complicated power-series expansion of the light-path function. The structure ...
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ISBN:
(纸本)0819443115
A novel newton recursive algorithm is proposed for an optimum design of arrayed waveguide gratings, which is different from the traditional complicated power-series expansion of the light-path function. The structure of an arrayed waveguide grating is represented by three constraint equations which may be chosen to meet some specific design demands. The new algorithm combines newtonalgorithm with structure nonlinear constraint functions, which makes it more general and flexible for the optimum design of the device. From the initial value given, the arrayed-waveguide positions and matched waveguide lengths are determined from the numerical solutions for the roots of three constraint equations through a newtonrecursive procedure in sequence. Anastigmatic mounts of arrayed waveguide gratings based on this algorithm are processed, and a three stigmatic-points one is designed. Further applications of this algorithm are also discussed, including the one that can not be designed with the theory of the power-series expansion of light-path function.
A kind of second order algorithm--recursive approximate newtonalgorithm was given by Karayiannis. The algorithm was simplified when it was formulated. Especially, the simplification to matrix Hessian was very reluct...
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A kind of second order algorithm--recursive approximate newtonalgorithm was given by Karayiannis. The algorithm was simplified when it was formulated. Especially, the simplification to matrix Hessian was very reluctant, which led to the loss of valuable information and affected performance of the algorithm to certain extent. For multi layer feed forward neural networks, the second order back propagation recursivealgorithm based generalized cost criteria was proposed. It is proved that it is equivalent to newton recursive algorithm and has a second order convergent rate. The performance and application prospect are analyzed. Lots of simulation experiments indicate that the calculation of the new algorithm is almost equivalent to the recursive least square multiple algorithm. The algorithm and selection of networks parameters are significant and the performance is more excellent than BP algorithm and the second order learning algorithm that was given by Karayiannis.
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