IDENTIFICATION OF CHAOTIC SYSTEMS WITH NOISY DATA BASED ON RBF NEURAL NETWORKS

摘要：

In this paper, we present that noisy chaotic systems can be identified with RBF neural networks. We design three-layers RBF network structure and clarify fundamental properties of RBF networks to learn noisy chaotic systems by some numerical experiments. We also evaluate the identified models with reconstruction of attractors by the identified models. Simulations show that the identified models can approach to original chaotic systems and extract dynamical characteristics of original chaotic systems.

关键词： Rbf neural networks Chaotic systems identification Noisy chaotic systems

作者: DONG-MEI LI FA-CHAO LI

作者单位: School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, China

会议类型: 国际会议

会议名称: 2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

会议地点: 保定

会议语种:英文

页码: 2578-2581

在线出版日期: 2009-07-12（万方平台首次上网日期，不代表论文的发表时间）