摘要
选用正态函数作为模糊变量的隶属函数 ,给出了基于Takagi_Sugeno模型的模糊神经网络的用于学习的性能指标 ,并对其性质进行了分析 .在此基础上将二阶段变半径随机搜索法用作模糊神经网络的学习算法 .这种方法简便易行 ,可使模糊神经网络达到较高的精度 .该文给出了神经网络记忆容量的定义并求出了基于TS模型的模糊神经网络的记忆容量 .
Taking normal functions as membership functions of the fuzzy neural network based on Takagi_Sugeno model, this paper gives a performance index used in learning and analysis its properties. Based on these results, an algorithm, called two-stage random search algorithm with Variable radius, is used in learning. A great many of examples show that the algorithm is simple and convenient and can make the fuzzy neural network obtain high precision. The definition of memory volume and the memory volume of a neural network based on Takagi_Sugeno model is given as well in this paper.
出处
《曲阜师范大学学报（自然科学版）》
CAS
2000年第2期4-7,共4页
Journal of Qufu Normal University(Natural Science)
基金
陕西省科委自然科学研究计划项目!( 98-SL0 8)
