Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published July 1988 | Published
Book Section - Chapter Open

High-capacity exponential associative memories

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.

Additional Information

© 1988 IEEE.

Attached Files

Published - 00023843.pdf

Files

00023843.pdf
Files (426.2 kB)
Name Size Download all
md5:e2d37bc9a15149fd77fc912258788a07
426.2 kB Preview Download

Additional details

Created:
August 19, 2023
Modified:
October 20, 2023