LEARNING ALGORITHM FOR A NEURAL NETWORK WITH BINARY SYNAPSES

被引：20
|
作者：
KOHLER, H
DIEDERICH, S
KINZEL, W
OPPER, M
机构：
[1] Institut für Theoretische Physik, Justus-Liebig-Universität, Giessen, D-6300
来源：
ZEITSCHRIFT FUR PHYSIK B-CONDENSED MATTER | 1990年 / 78卷 / 02期
关键词：
D O I：
10.1007/BF01307854
中图分类号：
O469 [凝聚态物理学];
学科分类号：
070205 ;
摘要：
A learning mechanism for neural networks with binary synapses is defined and investigated. The algorithm is based on minimizing the energy of an Ising model. A replica symmetric calculation gives a parameter range where perfect learning is possible. A simple descent algorithm is studied by numerical simulation; and storage capacities, learning times and basins of attraction are determined. © 1990 Springer-Verlag.
引用
收藏
页码：333 / 342
页数：10
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