@inproceedings{f1b51b5d37f548808de22fa0fe69670f,
title = "Searching real-valued synaptic weights of hopfield's associative memory using evolutionary programming",
abstract = "We apply evolutionary computations to Hopfield model of associative memory. Although there have been a lot of researches which apply evolutionary techniques to layered neural networks, their applications to Hopfield neural networks remain few so far. Previously we reported that a genetic Mgorithm using discrete encoding chromosomes evolves the Hehb-rule associative memory to enhance its storage capacity. We also reported that the genetic algorithm evolves a network with random synaptic weights eventually to store some number of patterns as fixed points. In this paper we present an evolution of the Hopfield model of associative memory using evolutionary programming as a reM-valued parameter optimization.",
author = "Akira Imada and Keijiro Araki",
year = "1997",
month = jan,
day = "1",
language = "English",
isbn = "9783540627883",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "13--22",
editor = "Angeline, {Peter J.} and Reynolds, {Robert G.} and McDonnell, {John R.} and Russ Eberhart",
booktitle = "Evolutionary Programming VI - 6th International Conference, EP 1997, Proceedings",
address = "Germany",
note = "6th International Conference on Evolutionary Programming, EP 1997 ; Conference date: 13-04-1997 Through 16-04-1997",
}