期刊论文

Li, Long

英文

Fuzzy Sets and Systems

0165-0114

2022

426

27-45

10.1016/j.fss.2020.11.003

Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [11401185]; Scientific Research Fund of Hunan Provincial Education DepartmentHunan Provincial Education Department [19A063, 17A031]; Science and Technology Plan Project of Hunan Province (Hunan Provincial Key Laboratory of Intelligent Information Processing and Application) [2016TP1020]; Science and Technology Plan Project of Hengyang City [2017KJ183]; Application-oriented Characterized Disciplines, Double First-Class University Project of Hunan Province [Xiangjiaotong [2018] 469]; China Scholarship CouncilChina Scholarship Council [201608430257]; 2019-2020 Hunan overseas distinguished professorship project [2019014]

本校为第一且通讯机构

Online gradient descent method has been widely applied for parameter learning in neuro-fuzzy systems. The success of the application relies on the convergence of the learning procedure. However, there barely have been convergence analyses on the online learning procedure for neuro-fuzzy systems. In this paper, an online gradient learning algorithm with adaptive learning rate is proposed to identify the parameters of the neuro-fuzzy systems representing the Mamdani fuzzy model with Gaussian fuzzy sets. We take the reciprocals of the variances of...