A wireless sensor network consists of a set of sensors S and a monitored set of targets (or an area) T. Typically, there are much more sensors than the targets, but their operation time is limited by the battery capac...
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The goal of this paper is to develop a parallel algorithm that, on input of a learning sample, identifies a regular language by means of a nondeterministic finite automaton (NFA). A sample is a pair of finite sets con...
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ISBN:
(数字)9781728189468
ISBN:
(纸本)9781728189475
The goal of this paper is to develop a parallel algorithm that, on input of a learning sample, identifies a regular language by means of a nondeterministic finite automaton (NFA). A sample is a pair of finite sets containing positive and negative examples. Given a sample, a minimal NFA or the range of possible sizes of such an NFA, that represents the target regular language is sought. We define the task of finding an NFA, which accepts all positive examples and rejects all negative ones, as a constraint satisfaction problem, and then propose a parallel algorithm to solve the problem. The results of computational experiments on the variety of test samples are reported.
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