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

页码：333 / 342

页数：10

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