A binary hopfield neural-network approach for satellite broadcast scheduling problems

被引：20

作者：

Funabiki, N

Nishikawa, S

机构：

[1] Department of Information and Computer Sciences, Faculty of Engineering Science, Osaka University, Toyonaka

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 1997年 / 8卷 / 02期

关键词：

binary neuron; combinatorial optimization; heuristic method; neural network; parallel computation; satellite broadcast scheduling; simulation;

D O I：

10.1109/72.557699

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a binary Hopfield neural network approach for finding a broadcasting schedule in a low-altitude satellite system. Our neural network is composed of simple binary neurons on the synchronous parallel computation, which is greatly suitable for implementation on a digital machine. With the help of heuristic methods, the neural network of a maximum of 200 000 neurons can always find near-optimum solutions on a conventional work station in our simulations.

引用

页码：441 / 445

页数：5

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