@inproceedings{26df7faca74a4158af0357d618a9fae7,
title = "Random perturbations to hebbian synapses of associative memory using a genetic algorithm",
abstract = "We apply evolutionary algorithms to Hopfield model of associative memory. Previously we reported that. a genetic algorithm using ternary chromosomes evolves the Hebb-rule associative memory to enhance its storage capacity by pruning some connections. This paper describes a genetic algorithm using real- encoded chromosomes which successfully evolves over-loaded Hebbian synaptic weights to function as an associative memory. The goal of this study is to shed new light on the analysis of the Hopfield model, which also enables us to use the model as more challenging test suite for evolutionary computations.",
author = "Akira Imada and Keijiro Araki",
year = "1997",
doi = "10.1007/bfb0032498",
language = "English",
isbn = "3540630473",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "398--407",
booktitle = "Biological and Artificial Computation",
address = "Germany",
note = "4th International Work-Conference on Artificial and Natural Neural Networks, IWANN 1997 ; Conference date: 04-06-1997 Through 06-06-1997",
}