1993
DOI: 10.1016/0097-8493(93)90079-o
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Image compression using weighted finite automata

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Cited by 117 publications
(16 citation statements)
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“…This relaxation precisely corresponds to the use of a weighted automaton M W = (Q, Σ, λ, σ, ρ) where every transition, starting and finishing state has an associated, possibly intolerable, cost defined by the cost functions λ, σ and ρ [27]. The cost of an assignment in the decomposition is equal, by definition, to the cost of an optimal parse of the assignment by the weighted automaton.…”
Section: Berge-acyclicity and Directional Arc Consistencymentioning
confidence: 99%
“…This relaxation precisely corresponds to the use of a weighted automaton M W = (Q, Σ, λ, σ, ρ) where every transition, starting and finishing state has an associated, possibly intolerable, cost defined by the cost functions λ, σ and ρ [27]. The cost of an assignment in the decomposition is equal, by definition, to the cost of an optimal parse of the assignment by the weighted automaton.…”
Section: Berge-acyclicity and Directional Arc Consistencymentioning
confidence: 99%
“…Weighted automata (WA) are an expressible extension of finite state automata for computing functions over strings. They have been extensively studied since Schützenberger [25], and its decidability problems [16,1], extensions [9], logic characterization [9,15], and applications [20,8] have been deeply investigated.…”
Section: Introductionmentioning
confidence: 99%
“…The mathematical theory behind WFAs, that of rational power series, has been extensively studied in the past [28,53,38,14] and has been more recently the topic of a dedicated handbook [25]. WFAs are widely used in modern applications, perhaps most prominently in image processing and speech recognition where the terminology of weighted automata seems to have been first introduced and made popular [32,46,51,44,48], in several other speech processing applications such as speech synthesis [54,2], in phonological and morphological rule compilation [34,35,50], in parsing [47], machine translation [23], bioinformatics [27,3], sequence modeling and prediction [21], formal verification and model checking [5,4], in optical character recognition [17], and in many other areas.…”
Section: Introductionmentioning
confidence: 99%