IEEE Trans Neural Netw Learn Syst. 2017 Jul;28(7):1542-1549. doi: 10.1109/TNNLS.2016.2542205. Epub 2016 Apr 5.
In this paper, we present a novel approach for studying Boolean function in a graph-theoretic perspective. In particular, we first transform a Boolean function f of n variables into an induced subgraph H of the n -dimensional hypercube, and then, we show the properties of linearly separable Boolean functions on the basis of the analysis of the structure of H . We define a new class of graphs, called hyperstar, and prove that the induced subgraph H of any linearly separable Boolean function f is a hyperstar. The proposal of hyperstar helps us uncover a number of fundamental properties of linearly separable Boolean functions in this paper.
本文提出了一种从图论角度研究布尔函数的新方法。具体来说,我们首先将一个 n 变量的布尔函数 f 转换为 n 维超立方体的一个诱导子图 H,然后基于 H 的结构分析来展示线性可分布尔函数的性质。我们定义了一类新的图,称为超星图,并证明了任何线性可分布尔函数 f 的诱导子图 H 都是一个超星图。超星图的提出帮助我们揭示了本文中线性可分布尔函数的一些基本性质。