The performance characteristics of five variants of the Hopfield network are examined. Two performance metrics are used: memory capacity, and a measure of the size of basins of att...
We introduce a neural network with associative memory and a continuous topology, i.e. its processing units are elements of a continuous metric space and the state space is Euclide...
In this paper, image processing and symbol processing are bridged with a common framework. A new computational architecture allows arbitrary fixed images to be used as attractors ...
- A dynamical neural model that is strongly biologically motivated is applied to learning and retrieving binary patterns. This neural network, known as Freeman’s Ksets, is traine...
Attractor network models of cortical associative memory functions have developed considerably over the past few years. Here we show that we can improve them further, in terms of c...