CONVERGENCE TIME AND FINITE SIZE EFFECTS IN NEURAL NETWORKS

被引：25

作者：

KOHRING, GA

机构：

来源：

JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL | 1990年 / 23卷 / 11期

关键词：

D O I：

10.1088/0305-4470/23/11/047

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

The time needed for convergence to a stable state starting from an initial state having macroscopic overlap with a stored state is studied numerically for networks up to N=105 neurons. Although such systems are much larger than those traditionally used in studying neural networks, they are still too small to extract reliable information about the asymptotic behaviour of the convergence time.

引用

页码：2237 / 2241

页数：5

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