Delayed transiently chaotic neural networks and their application

Shyan Shiou Chen*

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

7 引文 斯高帕斯(Scopus)

摘要

In this paper, we propose a novel model, a delayed transiently chaotic neural network (DTCNN), and numerically confirm that the model performs better in finding the global minimum for the traveling salesman problem (TSP) than the traditional transiently chaotic neural network. The asymptotic stability and chaotic behavior of the dynamical system with time delay are fully discussed. We not only theoretically prove the existence of Marotto's chaos for the delayed neural network without the cooling schedule by geometrically constructing a transversal homoclinic orbit, but we also discuss the stability of nonautonomous delayed systems using LaSalle's invariance principle. The result of the application to the TSP by the DTCNN might further explain the importance of systems with time delays in the neural system.

原文英語
文章編號033125
期刊Chaos
19
發行號3
DOIs
出版狀態已發佈 - 2009

ASJC Scopus subject areas

  • 統計與非線性物理學
  • 數學物理學
  • 物理與天文學 (全部)
  • 應用數學

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