On the analysis of fuzzy string patterns with the help of extended and stochastic GDPLL(k) grammars
Two methods of the analysis of distorted (fuzzy) string patterns are presented. The methods are based on the use of GDPLL(k) grammars generating a large subclass of context sensitive languages. The first one utilizes error-correcting approach: a minimum distance measure is used for error-correcting parsing. The second one utilizes stochastic approach: the decision about the production to be applied in a derivation step is given according to the probability measure.
context sensitive languages error-correcting parsing syntactic pattern recognition distorted patterns stochastic grammars