title: STRIP--a strip-based neural-network growth algorithm for learning multiple-valued functions.
abstract: We consider the problem of synthesizing multiple-valued logic functions by neural networks. A genetic algorithm (GA) which finds the longest strip in V is a subset of K(n) is described. A strip contains points located between two parallel hyperplanes. Repeated application of GA partitions the space V into certain number of strips, each of them corresponding to a hidden unit. We construct two neural networks based on these hidden units and show that they correctly compute the given but arbitrary multiple-valued function. Preliminary experimental results are presented and discussed.
authors.affiliation: Computer Science Department, University of Windsor, Windsor, ONN9B 3P4, Canada. angom@cs.uwindsor.ca
authors.forename: A
authors.initials: A
authors.lastname: Ngom
authors.forename: I
authors.initials: I
authors.lastname: Stojmenović
authors.forename: V
authors.initials: V
authors.lastname: Milutinović