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 attraction. We find that the posttraining adjustment of processor thresholds has, at best, little or no effect on performance, and at worst a significant negative effect. The adoption of a local learning rule can, however, give rise to significant performance gains.
CITATION STYLE
Davey, N., & Hunt, S. P. (1999). The capacity and attractor basins of associative memory models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1606, pp. 330–339). Springer Verlag. https://doi.org/10.1007/BFb0098189
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