Deformed fuzzy automata for correcting imperfect strings of fuzzy symbols

Presents a fuzzy method for the recognition of strings of fuzzy symbols containing substitution, deletion, and insertion errors. As a preliminary step, we propose a fuzzy automaton to calculate a similarity value between strings. The adequate selection of fuzzy operations for computing the transitions of the fuzzy automaton allows us to obtain different string similarity definitions (including the Levenshtein distance). A deformed fuzzy automaton based on this fuzzy automaton is then introduced in order to handle strings of fuzzy symbols. The deformed fuzzy automaton enables the classification of such strings having an undetermined number of insertion, deletion and substitution errors. The selection of the parameters determining the deformed fuzzy automaton behavior would allow to implement recognizers adapted to different problems. The paper also presents algorithms that implement the deformed fuzzy automaton. Experimental results show good performance in correcting these kinds of errors.