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基于同伦(homotopy)关系的ARMAX模型的辨识算法 被引量:1

Homotopy approach to ARMAX model identification
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摘要 论述了采用同伦 (hom otopy)法辨识 ARMAX模型的问题 .在 ARMAX模型的辨识中 ,由于滑动平均(MA)噪音模型部分的存在 ,用以估计 ARMAX模型参数的误差函数不再是单峰的 ,因而常用的基于最优化的估计算法有被陷入局部最小点的危险 .本文提出一种基于同伦关系的算法来解决这个问题 ,其基本想法是建立 ARMAX模型参数的估计和 ARX模型参数的估计两者之间的同伦关系 .由于用以估计 ARX模型参数的误差函数是单峰的 ,因而没有局部最小点问题 ,这就使得有可能利用它们之间的同伦关系来解决 ARMAX模型参数的估计中的局部最小点问题 .详细描述了基于同伦关系的新辨识算法 ,并利用蒙特卡罗 (Monte Car-lo) This paper deals with the problem of identifying ARMAX model using homotopy approach. Because of the MA noise model part, the criterion function for ARMAX model identification is not always unimodal and an optimization based algorithm has a potential risk to be stuck at a local minimum. A homotopy approach is introduced to solve this problem. The idea is to construct a homotopy connection of the identification based on ARMAX model with the one based on ARX model.Monte Carlo simulations illustrate the effectiveness of the homotopy based method.
出处 《系统工程学报》 CSCD 2002年第3期199-206,共8页 Journal of Systems Engineering
关键词 ARMAX模型 预测误差算法 多峰性问题 同伦关系 系统辨识 遗传算法 ARMAX model prediction error method homotopy method multimodality problem
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  • 3Coulibaly P, AnctiI F, Bobee B. Daily reservoir inflow fore casting using artificial neural networks with stopped training approach [J]. Journal of Hydrology, 2000, 230 (3 4) : 244- 257.
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  • 5Cveticanin L. Homotopy-perturbation method for pure nonlinear differential equation[J]. Chaos, Solitons & Fractals, 2006,30(5) : 1221-1230.
  • 6何光彩,洪炳熔.前馈神经网络的一种非线性同伦综合学习算法[J].计算机应用研究,1999,16(9):9-10. 被引量:5

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