Accession Number : AD0743217

Title :   Stochastic Syntactic Analysis and Syntactic Pattern Recognition,

Corporate Author : PURDUE UNIV LAFAYETTE IND SCHOOL OF ELECTRICAL ENGINEERING

Personal Author(s) : Huang,T. ; Fu,K. S.

Report Date : FEB 1972

Pagination or Media Count : 115

Abstract : Stochastic syntactic analysis algorithms for the class of stochastic context-free programmed languages are proposed and their application to pattern classification demonstrated. The area of grammatical inference is briefly reviewed and the possible extension to the inference of stochastic grammars is also studied. A stochastic grammar is formed by assigning a probability to each production associated with a grammar which is a formal system used conveniently to specify a language. The problem of deciding whether or not a stochastic grammar is consistent is called the consistency problem of stochastic languages. It is not yet known whether or not the consistency problem is decidable for stochastic context-sensitive grammars, stochastic programmed grammars and stochastic indexed grammars. Two types of stochastic syntatic analysis algorithms are proposed for stochastic context-free programmed languages. (Author)

Descriptors :   (*PROGRAMMING LANGUAGES, *SYNTAX), (*PATTERN RECOGNITION, STOCHASTIC PROCESSES), CONTEXT FREE GRAMMARS, CONTEXT SENSITIVE GRAMMARS, DECISION THEORY, MATHEMATICAL LOGIC, ARTIFICIAL INTELLIGENCE, THEOREMS

Subject Categories : Linguistics
      Computer Programming and Software

Distribution Statement : APPROVED FOR PUBLIC RELEASE