IMPROVED ALGORITHM OF RBF NEURAL NETWORKS AND ITS APPLICATION

摘要：

　　In order to improve the predictive accuracy of RBF neural network in function approximation,an improved RBF neural network was proposed.In this new model,human experience was added to the last layer as the activation function.The model of improved algorithm was built in Simulink,and was used to approximate a 2-dimensional function.The simulation result showed that the improved network performed well in function approximation.At last,a neural network system which was based on the improved algorithm was used in license plate recognition.In this system,the first two layers of the network were implemented in hardware,and the last layer was achieved in software.Experimental results show that the predictive accuracy of network is improved after joining human experience to the output layer.

关键词： RBF neural networks Sample point Simulation Hardware neural network

作者: Dong Wei Yiqing Liu Ning Zhang Minzhe Zhao

作者单位: School of Electrical and Information Engineering Beijing University of Civil Engineering and Archite Kuga Technologies Co.,Ltd,Beijing 100036,China

会议类型: 国际会议

会议名称: 2012 2nd IEEE International Conference on Cloud Computing and Intelligence Systems (2012年第2届IEEE云计算与智能系统国际会议(IEEE CCIS2012))

会议地点: 杭州

会议语种:英文

页码: 1795-1799

在线出版日期: 2012-10-30（万方平台首次上网日期，不代表论文的发表时间）