USING NEURAL NETS TO LOOK FOR CHAOS

被引：34
作者：
ALBANO, AM [1 ]
PASSAMANTE, A [1 ]
HEDIGER, T [1 ]
FARRELL, ME [1 ]
机构：
[1] USN,AIR WARFARE CTR,WARMINSTER,PA 18974
来源：
PHYSICA D | 1992年 / 58卷 / 1-4期
关键词：
D O I：
10.1016/0167-2789(92)90098-8
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Backpropapting neural networks are used to reconstruct the attractors of two low-dimensional chaotic systems using small input sets of noise-corrupted data. The nets are able to reconstruct attractors that are visually similar to, and have the same correlation dimensions as, attractors constructed from noise-free data.
引用
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页码：1 / 9
页数：9
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