Title :
Stochastic Syntactic Decoding for Pattern Classification
Author :
Fung, Lai-wo ; Fu, King-Sun
Author_Institution :
School of Electrical Engineering, University of Tennessee
fDate :
6/1/1975 12:00:00 AM
Abstract :
A model of noise deformation of the substitution type is adopted for linguistic patterns generated by formal grammars. The maximum-likelihood criterion and the minimum-distance criterion are proposed for the classification of noisy strings described by context-free grammars. Classification algorithms based on a modified Cocke-Younger-Kasami parsing scheme are presented.
Keywords :
Error-correcting parsing (ECP), maximum-likelihood criterion, minimum-distance criterion, syntactic decoding, syntactic pattern recognition.; Classification algorithms; Decision making; Deformable models; Formal languages; Maximum likelihood decoding; Noise generators; Pattern classification; Pattern recognition; Stochastic processes; Stochastic resonance; Error-correcting parsing (ECP), maximum-likelihood criterion, minimum-distance criterion, syntactic decoding, syntactic pattern recognition.;
Journal_Title :
Computers, IEEE Transactions on
DOI :
10.1109/T-C.1975.224278
