一种广义模糊神经网络的参数解耦学习算法

Decoupled Learning Algorithm for a Generalized Fuzzy Neural Network

对于强非线性系统采用分段建模十分有效,广义模糊神经网络能实现这种思想。在此基础上,给出一种模糊规则前、后件参数可分别进行学习的算法,仿真结果表明该方法拟合能力强、学习效率高。

A strategy was presented for approximating a function by combining fuzzy neural networks with piecewise models. A decoupled learning algorithm was given. The condition and consequence of fuzzy rules can be separately trained. Computer simulation shows that the algorithm is feasible and efficient.