北京建筑工程学院学报2011，Vol.27Issue(4)：57-61,5.
基于Spiking的RBF神经网络故障诊断算法
Fault Diagnosis of RBF Neural Network Based on Spiking
霍一峰 1王亚慧1
作者信息
- 1. 北京建筑工程学院电气与信息工程学院,北京100044
- 折叠
摘要
Abstract
Neural network is one of the independent control methods,which need not the given priori knowledge and diagnosis function.Neural network has a good adaptability to the changing environment（including disturbance and noise signal,etc）.RBF neural network is a three layers feedforward network with one single hidden layer.The mapping from the input to the hidden layer is nonlinear and the mapping from the hidden layer to the output is linear.RBF neural network has a quick convergence rate,the uniqueness optimal approximation and will not fall into local minimum.Spiking neural network adopts time encoding to process data,which is more closed to the real biology nervous system.RBF neural network based on Spiking coding has a remarkable effect in forecast accuracy and error control.关键词
RBF神经网络/Spiking/故障诊断Key words
RBF neural network/Spiking/fault diagnosis分类
计算机与自动化引用本文复制引用
霍一峰,王亚慧..基于Spiking的RBF神经网络故障诊断算法[J].北京建筑工程学院学报,2011,27(4):57-61,5.
