正则表达式语言是小字母上局部函数的图像

IF 0.8 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Information and Computation Pub Date : 2024-07-31 DOI:10.1016/j.ic.2024.105206
Stefano Crespi Reghizzi , Pierluigi San Pietro
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引用次数: 0

摘要

通过使用严格局部可检验 (-slt) 语言和局部有理函数代替同态,扩展了正则表达式语言作为局部语言同态字母到字母图像的特征(又称梅德韦杰夫定理)。
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Regular languages as images of local functions over small alphabets

The characterization (a.k.a. Medvedev theorem) of regular languages as homomorphic letter-to-letter image of local languages, over an alphabet of cardinality depending on the recognizer size, is extended by using strictly locally testable (k-slt) languages, k>1, and a local rational function instead of a homomorphism.

By encoding DFA computations via comma-free codes, we prove that regular languages are the output of quasi-length-preserving local functions, defined on alphabets with one more letter than in the language. A binary alphabet suffices if the local function is allowed to shorten input length, or if the regular language has polynomial density.

If local relations are considered instead of functions, a binary input alphabet suffices for any regular language. A new simpler proof is then obtained of the extension of Medvedev's theorem stating that any regular language is the homomorphic image of an slt language over an alphabet of double size.

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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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