径向基函数神经网络在脑电信号建模中的应用

The Application of Radical Base Function Neural Networks in EEG Modeling

详细介绍了径向基函数神经网络在脑电信号建模中的应用 ,描述了径向基函数神经网络的结构与算法 ,通过与反向传播算法神经网络在脑电建模中的应用进行对比 。

Neural networks have many applications in scientific fields,especially in the non-linear system modeling(such as EEG signal). Back propagation algorithm(BP)and radical base function(RBF)neural networks have strong ability to simulate non-linear functions. So BP and RBF networks are both used in system modeling. In this paper,we introduced the application of RBF networks in EEG signal modeling,and described its architecture,transfer function and training algorithm. Through comparing with BP networks performance,we found that RBF networks needed less time and training steps to achieve better result in modeling a non-linear system, and RBF networks are more suitable for modeling a non-linear system such as EEG.