Data Filtering-Based Multi-innovation Stochastic Gradient Algorithm for Nonlinear Output Error Autoregressive Systems

Data Filtering-Based Multi-innovation Stochastic Gradient Algorithm for Nonlinear Output Error Autoregressive Systems
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基于数据滤波的非线性输出误差自回归系统多创新随机梯度算法

DOI:
10.1007/s00034-015-0064-y
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发表时间:
2015-05
影响因子:
2.3
通讯作者:
Ding, Feng
Ding, Feng
中科院分区:
工程技术3区
文献类型:
--
作者:
Mao, Yawen;Ding, Feng

文献摘要

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本文讨论了非线性输出误差自回归系统的参数估计问题,结合多创新辨识理论和数据滤波技术,提出了一种基于数据滤波的多创新随机梯度算法,提高了随机梯度算法的参数估计精度。与多创新随机梯度算法相比,该算法具有较高的参数估计精度。仿真结果证实了这一结论。
This paper discusses the parameter estimation problems of nonlinear output error autoregressive systems and presents a data filtering-based multi-innovation stochastic gradient algorithm for improving the parameter estimation accuracy of the stochastic gradient algorithm by combining the multi-innovation identification theory and the data filtering technique. The proposed algorithm is effective and can generate highly accurate parameter estimates compared with the multi-innovation stochastic gradient algorithm. The simulation results confirm this conclusion.
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