A new method to optimize the satellite broadcasting schedules using the mean field annealing of a Hopfield neural network

Author

Ansari, Nirwan ; Hou, Edwin S H ; Yu, Youyi

Author_Institution

Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA

Volume

6

Issue

2

fYear

1995

fDate

3/1/1995 12:00:00 AM

Firstpage

470

Lastpage

483

Abstract

Reports a new method for optimizing satellite broadcasting schedules based on the Hopfield 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

Keywords

Hopfield neural nets; direct broadcasting by satellite; field equations; iterative methods; scheduling; simulated annealing; telecommunication computing; television broadcasting; Hopfield neural network; associative matrix; clamping technique; critical temperature estimation; divergence; equation updating; iteration method; mean field annealing theory; numerical implementation; satellite broadcasting schedule optimization; solution space dimension reduction; Annealing; Artificial satellites; Clamps; Equations; Hopfield neural networks; Neural networks; Neurons; Optimization methods; Satellite broadcasting; Temperature;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/72.363481

Filename

363481