分组语言的运算状态复杂度
Operational State Complexity of Block Languages
AI总结:
该文研究分组语言上若干运算的确定性与非确定性状态复杂度,发现部分场景下其复杂度上界小于有限语言的通用上界,并提出位图是研究这类语言最小自动机与运算的有效工具。
摘要:
本文研究分组语言(即长度相同的单词构成的集合),并探讨这类语言上若干运算的确定性与非确定性状态复杂度。作为有限语言的子类,有限语言已知的运算状态复杂度上界同样适用于分组语言,但在多个场景中可得到更小的上界值。分组语言可表示为位图(bitmap),正如本文所展示的,位图是研究其最小有限自动机及相关运算的有效工具。
英文摘要:
In this paper we consider block languages, namely sets of words having the same length, and study the deterministic and nondeterministic state complexity of several operations on these languages. Being a subclass of finite languages, the upper bounds of operational state complexity known for finite languages apply for block languages as well. However, in several cases, smaller values were found. Block languages can be represented as bitmaps, which are a good tool to study their minimal finite automata and their operations, as we illustrate here.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。