Stability analysis of high-order Hopfield-type neural networks based on a new impulsive differential inequality

• Autorzy: Yang Liu , Rongjiang Yang , Jianquan Lu , Bo Wu , Xiushan Cai
• Języki publikacji: EN

Abstrakty

EN

This paper is devoted to studying the globally exponential stability of impulsive high-order Hopfield-type neural networks with time-varying delays. In the process of impulsive effect, nonlinear and delayed factors are simultaneously considered. A new impulsive differential inequality is derived based on the Lyapunov-Razumikhin method and some novel stability criteria are then given. These conditions, ensuring the global exponential stability, are simpler and less conservative than some of the previous results. Finally, two numerical examples are given to illustrate the advantages of the obtained results.

Słowa kluczowe

EN

impulsive differential inequality; globally exponential stability; high-order Hopfield-type neural network

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2013
• Tom: 23
• Numer: 1
• Strony: 201-211

Daty

wydano

2013

otrzymano

2011-12-31

poprawiono

2012-05-09

Twórcy

autor

Yang Liu

• College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China

autor

Rongjiang Yang

• College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China

autor

Jianquan Lu

• Department of Mathematics, Southeast University, Nanjing 210096, China

autor

Bo Wu

• College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China
• Academic Affairs Division, Zhejiang Normal University, Jinhua 321004, China

autor

Xiushan Cai

• College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China

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Identyfikatory

DOI

10.2478/amcs-2013-0016