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Titlebook: Automata Implementation; 4th International Wo Oliver Boldt,Helmut Jürgensen Conference proceedings 2001 Springer-Verlag Berlin Heidelberg 2

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An Algorithm to Verify Local Threshold Testability of Deterministic Finite Automata, the sets of substrings occurring . times are the same, for . ≤ .. For given . and . the language is called .-threshold ktestable. A finite deterministic automaton is called .-threshold .-testable.New version of polynomial time algorithm to verify the local testability will be presented too.
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FA Minimisation Heuristics for a Class of Finite Languages,n the context of Constraint Satisfaction Problems, widely used in AI. We first give some complexity results which are based on the strong relationship with covering problems of bipartite graphs. We then use these coverings as a basic tool for the definition of minimization heuristics, and describe s
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Analysis of Reactive Systems with , Timers,ls are equally adapted to numerical calculations as to symbolical ones, thus allowing for parametric analysis. The results we have obtained rely on a simple and efficient representation of the states of an automaton that recognizes the behaviors of the process. This representation is based on a mech
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Animation of the Generation and Computation of Finite Automata for Learning Software, not suffice. We have developed a learning software, that helps the learner to better understand principles of compiler construction, in particular lexical analysis. The software offers on the one hand an interactive introduction to the problems of lexical analysis, in which the most important defin
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Metric Lexical Analysis,at every additive quasi-distance is regularitypreserving, that is, the neighborhood of any radius of a regular language with respect to an additive quasi-distance is regular. As an application we present a simple algorithm that constructs a metric (fault-tolerant) lexical analyzer for any given lexi
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Treatment of Unknown Words,atization), or morphological categories (in tagging), or both. Some of them find their ways into dictionaries, and it would be nice to predict what their entries should look like. Humans can perform those tasks using endings of words (sometimes prefixes and infixes as well), and so can do computers.
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Computing Entropy Maps of Finite-Automaton-Encoded Binary Images,on and Hausdorff dimension of the encoded image. Jürgensen and Staiger [.] proposed a method by which the local Hausdorff dimension of the encoded image could be effectively computed. This paper describes the first implementation of this procedure and presents some experimental results showing local
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