摘要
Boole函数的线性可分和线性不可分问题,一直是前向人工神经网络的一个比较困难的问题,目前仅对变量数n≤7的线性可分问题给予过讨论。本文在文献[1]中所提出的n-维Boole函数分类复杂度定义的基础上,提出了n-维Boole函数容错分类复杂度的概念,并讨论了n-维超立方体的一些计数性质,给出了计数结果,从而为进一步讨论容错分类复杂度为2的Boole函数及其计数问题做了理论上的准备。
The linear and non-linear separability of Boolean functions are difficult problems, in which only linearly separable problem for dimension n ≤7 had ever been discussed. This paper, on the bases of classification complexity of n-dimensional Boo1ean functions, presents a concept of to1erantly lineat c1assification of n-dimensional Boolean functions , and discusses some counting properties of n-dimensional hypercubes with the counting results presented' A1l of these are refered as the theoretical preparation for the further discussion of Boolean functions of tolerantly linear separability to be 2.
出处
《微电子学与计算机》
CSCD
北大核心
1997年第3期26-29,共4页
Microelectronics & Computer
基金
北京大学视觉与听觉信息处理国家重点实验室资助
关键词
神经网络
非线性可分
布尔函数
前向网络
Feedforward neural network, Linearly separable and non-linearly separable, Classification complexity and tolerant classification complexity, N-dimensional hypercube,Boolean function