Accession Number : AD0709732

Title :   NONPARAMETRIC AND LINGUISTIC APPROACHES TO PATTERN RECOGNITION,

Corporate Author : PURDUE UNIV LAFAYETTE IND SCHOOL OF ELECTRICAL ENGINEERING

Personal Author(s) : Swain,Philip H. ; Fu,King Sun

Report Date : JUN 1970

Pagination or Media Count : 195

Abstract : The report investigates two approaches to pattern recognition which utilize information about pattern organization. First, a nonparametric method is developed for estimating the probability density functions associated with the pattern classes. The dispersion of the patterns in the feature space is used in attempting to optimize the estimate. The second approach involves the structural relationships of pattern components, an approach called 'linguistic' because it employs the concepts and methods of formal linguistics. The nonparametric density estimation technique is shown to produce acceptable results with real data and demonstrate a definite advantage over a parametric procedure when multimodal data is involved. Two alternative techniques are investigated for analyzing linguistic descriptions of patterns. Stochastic automata are considered as recognizers of stochastic pattern languages. The other technique is a stochastic generalization of the recently proposed programmed grammar which is developed as a grammar for pattern description. (Author)

Descriptors :   (*PATTERN RECOGNITION, STATISTICAL ANALYSIS), COMPUTATIONAL LINGUISTICS, PROBABILITY DENSITY FUNCTIONS, DISTRIBUTION FUNCTIONS, OPTIMIZATION, AUTOMATA

Subject Categories : Linguistics
      Cybernetics
      Bionics

Distribution Statement : APPROVED FOR PUBLIC RELEASE