论文部分内容阅读
提出T-S型模糊RBF神经网络模型结构,讨论该模型参数的输入空间模糊最优聚类学习算法.仿真结果验证了学习算法的有效性和可行性,表明T-S型模糊RBF神经网络可逼近任意多变量非线性函数.
The T-S fuzzy RBF neural network model structure is proposed, and the input space fuzzy optimal clustering learning algorithm of the model parameters is discussed. The simulation results verify the effectiveness and feasibility of the learning algorithm, indicating that T-S fuzzy RBF neural network can approximate any multivariable nonlinear function.