Automata theory and application

PUSH DOWN AUTOMATA research papers

Context-free language induction by evolution of deterministic push-down automata using genetic programming
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Abstract The process of learning often consists of Inductive Inference, making generalizations from samples. The problem here is finding generalizations (Grammars) for Formal Languages from finite sets of positive and negative sample sentences. The focus

Bounded push down automata
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The central problem of the theory of grammars and languages is that of determin ing for a given class S of languages a class of automata which accept exactly the languages in S. This problem was solved for regular events [l], linear languages , context-free

A redefinition of Embedded Push-Down Automata
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Abstract A new definition of Embedded Push-Down Automata is provided. We prove this new definition preserves the equivalence with tree adjoining languages and we provide a tabulation framework to execute any automaton in polynomial time with respect to the

Call Logging facilities using Push D Enhancement of User's Call Logging facilities usingPush Down Automata (PDA) with Real Time Automata (PDA) with Real
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Abstract This paper highlights the use of Push–Down Automata (PDA) in storing and maintaining the call logs. The special feature about this paper is to maintain incoming call record from the different mobile service provider in a mobile in clustered way to the user. It

Push Down Automata with 2 Stacks
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We can also think of these machines as algorithms. The states of this machine can be thought of as variables and the input string is the input given to the algorithm and the output for this algorithm would be whether the string is accepted or not. It does this by using the

Push-down Automata and Context-free Grammars
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This chapter details the design of push-down automata (PDA) for various languages, the conversion of CFGs to PDAs, and vice versa. In particular, after formally introducing push- down automata in Section 14.1, we introduce two notions of acceptance-by final state and

Theory and application of cellular automata for pattern classification
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This paper presents the theory and application of a high speed, low cost pattern classifier. The proposed classifier is built around a special class of sparse network referred to as Cellular Automata (CA). A specific class of CA, termed as Multiple Attractor Cellular 

Theory of automata and its application to psychology
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The firstthreelectures w111 dealwithlanguage processing, T heob J ectlveistounderstandn aturallanguage, especially OF children. T heemphasis 1 songrar~~ mzrandsemantics withthemaln accentonsemantics. T hesemantics w ill mainlybeconcernedwith model- 

A theory of ultimately periodic languages and automata with an application to time granularity
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ABSTRACT In this paper, we develop a theory of regular ?-languages that consist of ultimately periodic words only and we provide it with an automaton-based characterization. The resulting class of automata, called ultimately periodic automata (UPA), is a subclass of the 

Application of Fuzzy Automata Theory and Knowledge Based Neural Networks for Development of Basic Learning Model
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ABSTRACT The paper focuses on amalgamation of automata theory and fuzzy language. It uses adaptive knowledge basedABSTRACT framework which uses dynamic neural network framework along with fuzzy automata as Models of Learning, combining the two 

Genetic algorithms and application to adaptive automata for game theory
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This work is based on the usage of genetic algorithms. This kind of algorithms was proposed in the last decades (their origins are usually according to John Holland in the end of 1960s) as metaheuristics which goals are to obtain solutions to optimization problems. They can