Realization and bifurcation of boolean functions via Cellular Neural Networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

13 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)2109-2129
Journal / PublicationInternational Journal of Bifurcation and Chaos in Applied Sciences and Engineering
Volume15
Issue number7
Publication statusPublished - Jul 2005

Abstract

In this work, we study the realization and bifurcation of Boolean functions of four variables via a Cellular Neural Network (CNN). We characterize the basic relations between the genes and the offsets of an uncoupled CNN as well as the basis of the binary input vectors set. Based on the analysis, we have rigorously proved that there are exactly 1882 linearly separable Boolean functions of four variables, and found an effective method for realizing all linearly separable Boolean functions via an uncoupled CNN. Consequently, any kind of linearly separable Boolean function can be implemented by an uncoupled CNN, and all CNN genes that are associated with these Boolean functions, called the CNN gene bank of four variables, can be easily determined. Through this work, we will show that the standard CNN invented by Chua and Yang in 1988 indeed is very essential not only in terms of engineering applications but also in the sense of fundamental mathematics. © World Scientific Publishing Company.

Research Area(s)

  • Bifurcation, CNN, CNN gene, CNN gene bank, Linearly separable Boolean function