Approximate State Reduction of Fuzzy Finite Automata
Miroslav \'Ciri\'c (University of Ni\v{s}, Faculty of Sciences and, Mathematics, Ni\v{s}, Serbia), Ivana Mici\'c (University of Ni\v{s}, Faculty, of Sciences, Mathematics, Ni\v{s}, Serbia), Stefan Stanimirovi\'c, (University of Ni\v{s}, Faculty of Sciences, Mathematics, Ni\v{s},
TL;DR
This paper introduces approximate state reduction techniques for fuzzy finite automata, allowing behavior matching on all words up to a certain length, with four different reduction methods proposed.
Contribution
It presents a novel approach to approximate state reduction in fuzzy automata, relaxing the strict behavior equivalence requirement.
Findings
Four methods for approximate state reduction introduced
Behavior matching up to a specified word length achieved
Flexible reduction techniques for fuzzy automata developed
Abstract
In this paper we introduce a new type of approximate state reductions where the behaviors of the reduced and the original automaton do not have to be identical, but they must match on all words of length less than or equal to some given natural number. We provide four methods for performing such reductions.
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