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

Nobuo Funabiki, Seishi Nishikawa

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)441-445
Number of pages5
JournalIEEE Transactions on Neural Networks
Volume8
Issue number2
DOIs
Publication statusPublished - 1997
Externally publishedYes

Keywords

  • Binary neuron
  • Combinatorial optimization
  • Heuristic method
  • Neural network
  • Parallel computation
  • Satellite broadcast scheduling
  • Simulation

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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