Centre for Discrete and Applicable Mathematics
	CDAM Research Report, LSE-CDAM-2005-25 December 2005

Connections between Neural Networks and Boolean Functions

Martin Anthony

This report surveys some connections between Boolean functions and artificial neural networks. The focus is on cases in which the individual neurons are linear threshold neurons, sigmoid neurons, polynomial threshold neurons, or spiking neurons.

We explore the relationships between types of artificial neural network and classes of Boolean function. In particular, we investigate the type of Boolean functions a given type of network can compute, and how extensive or expressive the set of functions so computable is.

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