Title :
Storage Capacity of the Hopfield Network Associative Memory
Author :
Wu, Yue ; Hu, Jianqing ; Wu, Wei ; Zhou, Yong ; Du, K.L.
Author_Institution :
Enjoyor, Inc., Hangzhou, China
Abstract :
The Hop field model is a well-known dynamic associative-memory model. In this paper, we investigate various aspects of the Hop field model for associative memory. We conduct a systematic simulation investigation of several storage algorithms for Hop field networks, and conclude that the perceptron learning based storage algorithms can achieve much better storage capacity than the Hebbian learning based algorithms.
Keywords :
Hebbian learning; Hopfield neural nets; content-addressable storage; perceptrons; Hebbian learning based algorithms; Hopfield network associative memory; dynamic associative-memory model; perceptron learning based storage algorithms; storage capacity; Associative memory; Hebbian theory; Hopfield neural networks; Neurons; Training; Upper bound; Vectors; Hebbian learning; Hopfield model; associative memory; perceptron learning;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2012 Fifth International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-1-4673-0470-2
DOI :
10.1109/ICICTA.2012.89
