G-S Chaotic neural networks and its applications

摘要：

A novel G-S chaotic neural networks is proposed based on G-S chaotic neuron, whose structure is similar to BP neural networks. The activation function is no monotonous function and the neurons have two states. In the process of learning, the states of neurons are chaotic. According to the states, the weights can be adjusted. In the process of working, the sates of neurons are not chaotic. The learning algorithm of the networks is a chaos optimization method, which can get over the disadvantages of conventional networks. The function approximation and the hysteresis modeling of piezoelectric can be resolved by the networks. The experiment results proved the validity of the algorithm.

关键词： chaotic neural networks function approximation hysteresis modeling

作者: Guowei Xu

作者单位: School of Computer Science and Software Engineering Tianjin Polytechnic University Tianjin, China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

会议地点: 成都

会议语种:英文

页码: 120-122

在线出版日期: 2010-06-12（万方平台首次上网日期，不代表论文的发表时间）