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zbMATH Open
Article . 2011
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Fundamenta Informaticae
Article . 2011
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https://dx.doi.org/10.48550/ar...
Article . 2010
License: arXiv Non-Exclusive Distribution
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Transition Complexity of Incomplete DFAs

Transition complexity of incomplete DFAs
Authors: Yuan Gao; Kai Salomaa; Sheng Yu;

Transition Complexity of Incomplete DFAs

Abstract

We consider the transition complexity of regular languages based on the incomplete deterministic finite automata. We establish tight bounds for the transition complexity of Boolean operations, in the case of union the upper and lower bounds differ by a multiplicative constant two. We show that the transition complexity results for union and complementation are very different from the state complexity results for the same operations. However, for intersection, the transition complexity bounds turn out to be similar to the corresponding bounds for state complexity.

Keywords

FOS: Computer and information sciences, deterministic finite automaton, Formal Languages and Automata Theory (cs.FL), transition complexity, Computer Science - Formal Languages and Automata Theory, QA75.5-76.95, Formal languages and automata, regular languages, Boolean operations, Electronic computers. Computer science, QA1-939, incomplete automaton, Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Top 10%
Average
Green
gold