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

作者：Mao, Yawen; Ding, Feng^*

来源：Circuits, Systems, and Signal Processing, 2016, 35(2): 651-667.

DOI：10.1007/s00034-015-0064-y

• Stochastic gradient
• Multi-innovation identification theory
• Data filtering technique
• Nonlinear system

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.

• 出版日期2016-1
• 单位江南大学