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P. Garcia, E. Vidal, "Inference of kTestable Languages in the Strict Sense and Application to Syntactic Pattern Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 9, pp. 920925, September, 1990.  
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@article{ 10.1109/34.57687, author = {P. Garcia and E. Vidal}, title = {Inference of kTestable Languages in the Strict Sense and Application to Syntactic Pattern Recognition}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {12}, number = {9}, issn = {01628828}, year = {1990}, pages = {920925}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.57687}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Inference of kTestable Languages in the Strict Sense and Application to Syntactic Pattern Recognition IS  9 SN  01628828 SP920 EP925 EPD  920925 A1  P. Garcia, A1  E. Vidal, PY  1990 KW  ktestable languages; syntactic pattern recognition; inductive inference; strings; deterministic finitestate automation; inference algorithm; grammars; computational complexity; finite automata; formal languages; grammars; inference mechanisms; pattern recognition VL  12 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
The inductive inference of the class of ktestable languages in the strict sense (kTSSL) is considered. A kTSSL is essentially defined by a finite set of substrings of length k that are permitted to appear in the strings of the language. Given a positive sample R of strings of an unknown language, a deterministic finitestate automation that recognizes the smallest kTSSL containing R is obtained. The inferred automation is shown to have a number of transitions bounded by O(m) where m is the number of substrings defining this kTSSL, and the inference algorithm works in O(kn log m) where n is the sum of the lengths of all the strings in R. The proposed methods are illustrated through syntactic pattern recognition experiments in which a number of strings generated by ten given (source) nonkTSSL grammars are used to infer ten kTSSL stochastic automata, which are further used to classify new strings generated by the same source grammars. The results of these experiments are consistent with the theory and show the ability of (stochastic) kTSSLs to approach other classes of regular languages.
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