摘要
本文引进了集值函数的ｓ－可微和模糊值（Ｆ值）函数的Ｆｓ－可微概念。给出了这两种可微性的几个判别条件。最后研究并得到了一类模糊神经网络（ＦＮＮ）的Ｆｓ－可微性和连续性。
In the paper, we introduce s-differentiability of set-valued function and Fs-differen tiability of fuzzy valued (F-valued) function. And give a few of criterion conditions of the two differentiabilities. Finally, we discuss the Fs-differentiabilities and continuities of a class of fuzzy neural networks (FNNs).
出处
《模糊系统与数学》
CSCD
1996年第4期35-43,共9页
Fuzzy Systems and Mathematics
基金
国防预研基金
关键词
集值函数
微分
模糊神经网络
F值函数
Support function
s-differentiable
Fs-differentiable
fuzzy neural network
