High-capacity exponential associative memories.
Journal
Proceedings of International Conference on Neural Networks (ICNN'88), San Diego, CA, USA, July 24-27, 1988
Pages
153-160
Date Issued
1988
Author(s)
Abstract
A generalized associative memory model with potentially high capacity is presented. A memory of this kind with M stored vectors of length N, can be implemented with M nonlinear neurons, N ordinary thresholding neurons, and 2MN binary synapses. It is shown that special cases of this model include the Hopfield and high-order correlation memories. A special case of the model, based on a neuron which can implement the subthreshold region, is presented. The authors analyze the capacity of this exponentially associative memory and show that it scales exponentially with N. In any practical realization, however, the dynamic range of the exponentiators is constrained. They show that the capacity for networks with fixed dynamic range exponential circuits is proportional to the dynamic range.>
Type
conference paper