文献类型：期刊文献

英文题名：Dynamic system modeling based on wavelet recurrent fuzzy neural network

作者：Song, Ji-Rong[1]; Shi, Hong-Bo[2]

机构：[1] Department of Electronics and Communication Engineering, East China University of Science and Technology, Shanghai, China; [2] Department of Automation, East China University of Science and Technology, Shanghai, China

年份：2011

卷号：2

起止页码：766

外文期刊名：Proceedings - 2011 7th International Conference on Natural Computation, ICNC 2011

收录：EI(收录号：20114014404343)

语种：英文

外文关键词：Parameter estimation - Nonlinear dynamical systems - Fuzzy inference - Dynamical systems - Fuzzy neural networks

摘要：In this paper, Combined recurrent neural network and wavelet-based fuzzy neural network, A new wavelet recurrent fuzzy network (WRFNN) is presented. In order to simplify parameters identification and improve model generalization ability, The premise and consequent coefficients are optimized separately. The premise parameters are optimized by LM algorithm, at the same time the consequent coefficients are updated by recursive least square estimation. Simulation results of a nonlinear dynamic system and a CSTR system modeling show that the WRFNN can catch system dynamic real-time. ? 2011 IEEE.