2016
DOI: 10.3233/ifs-151828
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Minimal realization for fuzzy behaviour: A bicategory-theoretic approach

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Cited by 15 publications
(5 citation statements)
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“…Other directions of future scope of study done in this paper are to study minimal realization of fuzzy multiset finite automata, where membership structure of fuzzy sets may be algebraic structures different from [0, 1] and distributive lattices keeping in the mind the fact that the nature of input sets (crisp set [19,20], fuzzy sets [101], multisets [47,51]) and structure of membership values ([0,1][20], poset, distributive lattice [102], residuated lattice [103,104], LSET [47]) of fuzzy automata play a very important role in characterization of various concepts in different versions of fuzzy automata, i.e., the properties of fuzzy automata which hold with one membership structure of fuzzy sets may not hold with other membership structures of fuzzy sets, e.g., categorical characterizations of concepts associated with fuzzy multiset finite automata studied in sections 5 and onwards of [47] do not simply holds if we change membership structure of fuzzy sets from LSET to any one of the structures [0, 1], arbitrary sets, posets, distributive lattice or complete residuated lattices because of role of functor U defined in proposition 10 of [47]. The relationship of categorical concepts with automata theory (cf., [62,[105][106][107][108][109][110]) and partial order sets [105]) are well known, such study may be carried out in case of FMFA and posets/lattice structures associated with FMFA introduced in this paper.…”
Section: Discussionmentioning
confidence: 99%
“…Other directions of future scope of study done in this paper are to study minimal realization of fuzzy multiset finite automata, where membership structure of fuzzy sets may be algebraic structures different from [0, 1] and distributive lattices keeping in the mind the fact that the nature of input sets (crisp set [19,20], fuzzy sets [101], multisets [47,51]) and structure of membership values ([0,1][20], poset, distributive lattice [102], residuated lattice [103,104], LSET [47]) of fuzzy automata play a very important role in characterization of various concepts in different versions of fuzzy automata, i.e., the properties of fuzzy automata which hold with one membership structure of fuzzy sets may not hold with other membership structures of fuzzy sets, e.g., categorical characterizations of concepts associated with fuzzy multiset finite automata studied in sections 5 and onwards of [47] do not simply holds if we change membership structure of fuzzy sets from LSET to any one of the structures [0, 1], arbitrary sets, posets, distributive lattice or complete residuated lattices because of role of functor U defined in proposition 10 of [47]. The relationship of categorical concepts with automata theory (cf., [62,[105][106][107][108][109][110]) and partial order sets [105]) are well known, such study may be carried out in case of FMFA and posets/lattice structures associated with FMFA introduced in this paper.…”
Section: Discussionmentioning
confidence: 99%
“…In this section, we recall the concepts related to residuated lattices [5,39]; L-fuzzy relations [24,39]; L-fuzzy automata [7,23,36]; L-fuzzy languages [7,39], and Lfuzzy objects [23,24].…”
Section: Preliminariesmentioning
confidence: 99%
“…Proposition 2.1. [19,39] Let (L, ∧, ∨, , →, 0, 1) be a complete residuated lattice. Then for all x, y, z, x j , y j ∈ L and j ∈ Λ, the following properties hold:…”
Section: Preliminariesmentioning
confidence: 99%
“…The algebraic aspects of fuzzy automata and languages have been studied in [32,51]. The minimal realization problem of fuzzy languages has been studied algebraically in [21], by category-theoretic approach in [50,53,55], and in bicategory theoretic setting in [52,54,63] to brings closer the gap between classical automata theory and natural languages. The fuzzy automata and languages have been shown helpful in many applications like supervisory control [43], learning systems [60], heart problem deduction [8].…”
Section: Introductionmentioning
confidence: 99%