摘要
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．
A new type of Takagi Sugeno (T S) fuzzy radial basis function (RBF) in neural network is presented. A fuzzy optimum cluster algorithm in the input space is discussed. The simulation results show that the T S fuzzy RBF neural network approximates nonlinear function with any multi variable with any degree of accuracy, verifying the cluster algorithm being effective and available.
出处
《华中理工大学学报》
CSCD
北大核心
1999年第1期11-13,共3页
Journal of Huazhong University of Science and Technology
基金
广东省自然科学基金
