Journalartikel

More on deterministic and nondeterministic finite cover automata


AutorenlisteGruber, Hermann; Holzer, Markus; Jakobi, Sebastian

Jahr der Veröffentlichung2017

Seiten18-30

ZeitschriftTheoretical Computer Science

Bandnummer679

ISSN0304-3975

eISSN1879-2294

Open Access StatusBronze

DOI Linkhttps://doi.org/10.1016/j.tcs.2016.10.006

VerlagElsevier


Abstract
Finite languages are an important sub-regular language family, which were intensively studied during the last two decades in particular from a descriptional complexity perspective. An important contribution to the theory of finite languages are the deterministic and the recently introduced nondeterministic finite cover automata (DFCAs and NFCAs, respectively) as an alternative representation of finite languages by ordinary finite automata. We compare these two types of cover automata from a descriptional complexity point of view, showing that these devices have a lot in common with ordinary finite automata. In particular, we study how to adapt lower bound techniques for nondeterministic finite automata to NFCAs such as, e.g., the biclique edge cover technique, solving an open problem from the literature. Moreover, the trade-off of conversions between DFCAs and NFCAs as well as between finite cover automata and ordinary finite automata are investigated. Finally, we present some results on the average size of finite cover automata. (C) 2016 Published by Elsevier B.V.



Zitierstile

Harvard-ZitierstilGruber, H., Holzer, M. and Jakobi, S. (2017) More on deterministic and nondeterministic finite cover automata, Theoretical Computer Science, 679, pp. 18-30. https://doi.org/10.1016/j.tcs.2016.10.006

APA-ZitierstilGruber, H., Holzer, M., & Jakobi, S. (2017). More on deterministic and nondeterministic finite cover automata. Theoretical Computer Science. 679, 18-30. https://doi.org/10.1016/j.tcs.2016.10.006



Schlagwörter


AVERAGE STATEAverage state complexityBOUNDSEQUIVALENCEFinite languagesLANGUAGESLower bound techniques(Nondeterministic) cover automataSIMILARITY RELATIONSState complexity


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