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

Nobuo Funabiki, Seishi Nishikawa

Research output: Contribution to journalArticle

20 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

Fingerprint

Hopfield neural networks
Hopfield Neural Network
Broadcast
Neurons
Scheduling Problem
Neuron
Scheduling
Satellites
Neural Networks
Binary
Neural networks
Heuristic methods
Parallel Computation
Heuristic Method
Broadcasting
Schedule
Simulation

Keywords

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

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Hardware and Architecture

Cite this

A binary Hopfield neural-network approach for satellite broadcast scheduling problems. / Funabiki, Nobuo; Nishikawa, Seishi.

In: IEEE Transactions on Neural Networks, Vol. 8, No. 2, 1997, p. 441-445.

Research output: Contribution to journalArticle

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