Boolean function complexity and neural networks

Authors:
Ali Assi;P. W. C. Prasad;Azam Beg
Affiliations:
Department of Electrical Engineering, United Arab Emirates, University, UAE;College of Information Technology, United Arab Emirates, University, UAE;College of Information Technology, United Arab Emirates, University, UAE
Venue:
NN'06 Proceedings of the 7th WSEAS International Conference on Neural Networks
Year:
2006

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Abstract

A new neural network (NN) approach is proposed in this paper to estimate the Boolean function (BF) complexity. Large number of randomly generated single output BFs has been used and experimental results show good correlation between the theoretical results and those predicted by the NN model. The proposed model is capable of predicting the number of product terms (NPT) in the BF that gives an indication on its complexity.