基于粗糙集理论的有限自动机最小化方法改进

The Minimizing Method for Deterministic Finite State Automata Based on Rough Set Theory

有限自动机放在粗糙集的范畴中来研究,它的各个状态对应粗糙集论域中的每个对象,每个输入符号为一个等价关系。从粗糙集的角度,利用对论域进行知识划分的方法,每次产生新的等价类,直到每个等价类都不能划分为止,从而得到最小化的有限自动机。与已有的研究方法不同,该方法以粗糙集理论为工具,为有限自动机最小化方法研究提供了新的思路。

The DFA （deterministic finite state automata） is researched in the category of rough set, and its various states correspond to one object in the rough domain and each input symbol is recognized as one equivalence relation. Using knowledge partition method for the domain, each time new equivalence class will come out until each equivalence class cannot be parted. Different from other methods, this new idea is brought out for the research on minimizing the DFA based on the rough set.