Information content of neural networks with self-control and variable activity

被引：0

作者：

Bollé, D ^{[1
]}

Amari, SI ^{[1
]}

Carreta, DRCD ^{[1
]}

Massolo, G ^{[1
]}

机构：

[1] Katholieke Univ Leuven, Inst Theoret Fys, B-3001 Louvain, Belgium

来源：

DISORDERED AND COMPLEX SYSTEMS | 2001年 / 553卷

关键词：

D O I：

暂无

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

A self-control mechanism for the dynamics of neural networks with variable activity is discussed using a recursive scheme for the time evolution of the local field. It is based upon the introduction of a self-adapting time-dependent threshold as a function of both the neural and pattern activity in the network. This mechanism leads to an improvement of the information content of the network as well as an increase of the storage capacity and the basins of attraction. Different architectures are considered and the results are compared with numerical simulations.

引用

页码：11 / 16

页数：4

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