A New Method to Optimize the Satellite Broadcasting Schedules Using the Mean Field Annealing of a Hopfield Neural Network

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Abstract

This paper reports a new method for optimizing satellite broadcasting schedules based on the Hoplield neural model in combination with the mean field annealing theory. A clamping technique is used with an associative matrix, thus reducing the dimensions of the solution space. A formula for estimating the critical temperature for the mean field annealing procedure is derived, hence enabling the updating of the mean field theory equations to be more economical. Several factors on the numerical implementation of the mean field equations using a straightforward iteration method that may cause divergence are discussed; methods to avoid this kind of divergence are also proposed. Excellent results are consistently found for problems of various sizes.

Original languageEnglish (US)
Pages (from-to)470-483
Number of pages14
JournalIEEE Transactions on Neural Networks
Volume6
Issue number2
DOIs
StatePublished - Mar 1995

All Science Journal Classification (ASJC) codes

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

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