A NEW METHOD TO OPTIMIZE THE SATELLITE BROADCASTING SCHEDULES USING THE MEAN-FIELD

被引：31

作者：

ANSARI, N ^{[1
]}

HOU, ESH ^{[1
]}

YU, YY ^{[1
]}

机构：

[1] NEW JERSEY INST TECHNOL,CTR ELECTR IMAGING,NEWARK,NJ 07102

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 1995年 / 6卷 / 02期

关键词：

D O I：

10.1109/72.363481

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 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.

引用

页码：470 / 483

页数：14

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