Stochastic Syntactic Analysis and Syntactic Pattern Recognition,
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)
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 01, 1972
- Accession Number
- AD0743217
Entities
People
- King Sun Fu
- Tong Huang
Organizations
- Purdue University