计算机应用与软件Issue(10)：168-171,4.DOI:10.3969/j.issn.1000-386x.2015.10.039
基于 Hammerstein 型神经网络的非线性动态系统辨识
NONLINEAR DYNAMIC SYSTEM IDENTIFICATION BASED ON HAMMERSTEIN-TYPE NEURAL NETWORK
摘要
Abstract
Hammerstein model is widely applied to the identification of nonlinear systems,which consists of a nonlinear static gain part in cascade with a linear dynamic part.We propose a Hammerstein-type neural network (HNN)to simulate the conventional Hammerstein model,and apply it in the identification of nonlinear dynamic systems.The Lipschitz entropy is employed to determine the order of HNN,and the back-propagation (BP)algorithm is used for training the network weights.Simulation results show that HNN has satisfied identification performance on nonlinear dynamic systems.关键词
神经网络/系统辨识/Hammerstein 模型/非线性动态系统Key words
Neural network/System identification/Hammerstein-type neural network/Nonlinear dynamic system分类
信息技术与安全科学引用本文复制引用
慕昆,彭金柱..基于 Hammerstein 型神经网络的非线性动态系统辨识[J].计算机应用与软件,2015,(10):168-171,4.基金项目
高等学校博士学科点专项科研基金项目（20124101120001）；中国博士后科学基金项目（2013M541992）；河南省博士后基金项目（2013073）；河南省教育厅科学技术研究重点项目（14 A413009）。 （）
