Some Theoretical Properties of a Network of Discretely Firing Neurons

Abstract

The problem of optimising a network of discretely firing neurons is addressed. An objective function is introduced which measures the average number of bits that are needed for the network to encode its state. When this is minimised, it is shown that this leads to a number of results, such as topographic mappings, piecewise linear dependence on the input of the probability of a neuron firing, and factorial encoder networks.