Accession Number : ADA113934

Title :   The Use of Database Techniques in the Implementation of a Syntactic Pattern Recognition Task on a Parallel Reconfigurable Machine.

Descriptive Note : Master's thesis,

Corporate Author : PURDUE UNIV LAFAYETTE IN SCHOOL OF ELECTRICAL ENGINEERING

Personal Author(s) : Seed,Elizabeth Cathro ; Siegel,Howard Jay

PDF Url : ADA113934

Report Date : Dec 1981

Pagination or Media Count : 110

Abstract : Use of syntactic pattern recognition has been shown to be an effective technique for picture processing; it is, however, computationally time-consuming. The way in which a paralled SIMD/MIMD machine, PASM, can be used to decrease the processing time of these tasks is examined. Paralled machines have been used predominantly for decreasing the processing time of numerical problems in which the data is frequently well-ordered. In contrast, a syntactic pattern recognition task would use a parallel machine to perform multiple search, comparison, and string manipulator operations on some relatively complex data structures. A solution to the problem of implementing a specific parallel syntactic pattern recognition task, a parallel tree automaton, through the use of a relational database and relational language is proposed. Use of a CODASYL database and database language is also investigated. Two algorithms for implementing the parallel tree automaton are described. The problem of obtaining a reasonable processor and data allocation scheme for the two algorithms and for the two relational programs derived from the two algorithms is discussed. A comparison of the different problems posed by each algorithm is made.

Descriptors :   *Pattern recognition, *Parallel processors, Data bases, Syntax, Configurations, Pictures, Programming languages, Algorithms, Microprocessors, Reduction, High level languages, Comparison

Subject Categories : Computer Programming and Software
      Computer Hardware
      Human Factors Engineering & Man Machine System

Distribution Statement : APPROVED FOR PUBLIC RELEASE