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ω-automaton

About: ω-automaton is a research topic. Over the lifetime, 2299 publications have been published within this topic receiving 68468 citations. The topic is also known as: stream automaton & ω-automata.


Papers
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Journal ArticleDOI
TL;DR: The minimization problem of probabilistic and quantum automata is reduced to finding a solution of a system of algebraic polynomial (in)equations and the state minimization is shown to be decidable and in EXPSPACE.
Abstract: Several types of automata, such as probabilistic and quantum automata, require to work with real and complex numbers. For such automata the acceptance of an input is quantified with a probability. There are plenty of results in the literature addressing the complexity of checking the equivalence of these automata, that is, checking whether two automata accept all inputs with the same probability. On the other hand, the critical problem of finding the minimal automata equivalent to a given one has been left open [C. Moore, J.P. Crutchfield, Quantum automata and quantum grammars, Theoret. Comput. Sci. 237 (2000) 275-306, see p. 304, Problem 5]. In this work, we reduce the minimization problem of probabilistic and quantum automata to finding a solution of a system of algebraic polynomial (in)equations. An EXPSPACE upper bound on the complexity of the minimization problem is derived by applying [email protected]?s algorithm. More specifically, we show that the state minimization of probabilistic automata, measure-once quantum automata, measure-many quantum automata, measure-once generalized quantum automata, and measure-many generalized quantum automata is decidable and in EXPSPACE. Finally, we also solve an open problem concerning minimal covering of stochastic sequential machines [A. Paz, Introduction to Probabilistic Automata, Academic Press, New York, 1971, p. 43].

35 citations

Book ChapterDOI
25 Aug 1997
TL;DR: An explicit and efficiently computable formula is given for the inverse of D-dimensional linear cellular automata over Zm (D ≥ 1, m ≥ 2) to get an easy-to-check necessary and sufficient condition for an invertible 1-dimensionallinear CA to be expansive.
Abstract: We give an explicit and efficiently computable formula for the inverse of D-dimensional linear cellular automata over Zm (D ≥ 1, m ≥ 2). We use this formula to get an easy-to-check necessary and sufficient condition for an invertible 1-dimensional linear CA to be expansive.

35 citations

Book ChapterDOI
08 Jul 2002
TL;DR: This paper gives in this paper a method to compute a reversible automaton from the minimal automaton of a reversible language that contains an equivalent automaton which is quasi-reversible.
Abstract: Reversible languages occur in many different domains Although the decision for the membership of reversible languages was solved in 1992 by Pin, an effective construction of a reversible automaton for a reversible language was still unknown We give in this paper a method to compute a reversible automaton from the minimal automaton of a reversible language With this intention, we use the universal automaton of the language that can be obtained from the minimal automaton and that contains an equivalent automaton which is quasi-reversible This quasi-reversible automaton has nearly the same properties as a reversible one and can easily be turned into a reversible automaton

35 citations

14 May 2007
TL;DR: The results are promising and show that learning a real-time automaton directly from timed data outperforms a method that uses sampling in order to deal with the timed data.
Abstract: We describe an algorithm for learning simple timed automata, known as real-time automata. The transitions of real-time automata can have a temporal constraint on the time of occurrence of the current symbol relative to the previous symbol. The learning algorithm is similar to the redblue fringe state-merging algorithm for the problem of learning deterministic finite automata. In addition to state merges, our algorithm can perform state splits by making use of the time values in the input data. We tested our learning algorithm on randomly generated problems. The results are promising and show that learning a real-time automaton directly from timed data outperforms a method that uses sampling in order to deal with the timed data.

35 citations

Journal ArticleDOI
TL;DR: The concept of cover automata for finite languages was formally introduced in [3], and an algorithm was given to solve the inequality of the following type: For α ≥ 1, β ≥ 1 using LaSalle's inequality.
Abstract: The concept of cover automata for finite languages was formally introduced in [3]. Cover automata have been studied as an efficient representation of finite languages. In [3], an algorithm was give...

35 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20238
202219
20201
20191
20185
201748