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STRIP - a strip-based neural-network growth algorithm for learning multiple-valued functions

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3 Author(s)
A. Ngom ; Dept. of Comput. Sci., Windsor Univ., Ont., Canada ; I. Stojmenovic ; V. Milutinovic

We consider the problem of synthesizing multiple-valued logic functions by neural networks. A genetic algorithm (GA) which finds the longest strip in V⊆Kn 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

Published in:

IEEE Transactions on Neural Networks  (Volume:12 ,  Issue: 2 )