Accession Number : ADA327931
Title : Application of Genetic Algorithms to Function Decomposition in Pattern Theory.
Descriptive Note : Interim rept. Jan-Aug 93,
Corporate Author : WRIGHT LAB WRIGHT-PATTERSON AFB OH AVIONICS DIRECTORATE
Personal Author(s) : Noviskey, Michael J. ; Ross, Timothy D. ; Gadd, David A. ; Axtell, Mark
PDF Url : ADA327931
Report Date : 26 JAN 1994
Pagination or Media Count : 84
Abstract : This report documents use of genetic algorithms for finding partitions which lead to optimal decomposition of boolean functions in the Ashenhurst-Curtis method of functional decomposition. This problem apparently grows exponentially as the number of input variables increase, but is useful to study since it has a myriad of potential applications in algorithm design, circuit design, image processing, data compression, logic minimization, and machine learning. The report presents some background on function decomposition, genetic algorithms and results of some experiments. Although use of genetic algorithms still result in exponential growth; they provide a much lower rate of growth.
Descriptors : *ALGORITHMS, *COMPUTER PROGRAMMING, *PATTERN RECOGNITION, IMAGE PROCESSING, OPTIMIZATION, COMPUTER LOGIC, LEARNING MACHINES, HEURISTIC METHODS, DATA COMPRESSION, BOOLEAN ALGEBRA, BINARY NOTATION.
Subject Categories : Computer Programming and Software
Distribution Statement : APPROVED FOR PUBLIC RELEASE