| 时标上一类神经网络的指数同步(英文) |
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| 引用本文： | 杜德军,陈安平.时标上一类神经网络的指数同步(英文)[J].湘南学院学报,2008,29(2):6-12. |
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| 作者姓名： | 杜德军 陈安平 |
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| 作者单位： | 1. 湘潭大学,数学与计算科学学院,湖南,湘谭,411005
2. 湘潭大学,数学与计算科学学院,湖南,湘谭,411005;湘南学院,数学系,湖南,郴州,423000 |
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| 摘 要： | 基于时标微积分学理论和Lyapunov泛函,我们得到了时标上一类神经网络指数同步的充分条件,这些条件在应用上容易用代数方法检验因而意义重大,我们的结果统一和推广一些连续神经网络和对应的离散情形的相关结论.
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| 关 键 词： | 指数同步 神经网络 时标微积分学 时滞 Lyapunov泛函 exponential synchronization neural network time scales calculus delayed Lyapunov functions. 时标 类神经网络 指数同步 Time Neural Network Class Synchronization results extend continuous neural networks discrete analogues sufficient conditions significance practice simple algebraic method derived exponential |
Exponential Synchronization of a Class of Neural Network on Time Scaales |
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| DU De-jun,CHEN An-ping.Exponential Synchronization of a Class of Neural Network on Time Scaales[J].Journal of Xiangnan University,2008,29(2):6-12. |
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| Authors: | DU De-jun CHEN An-ping |
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| Institution: | DU De-jun1,CHEN Ap-ping1,2 (1 School of Mathematics , Computational Science,Xiangtan University,Xiangtan 411005,China,2 Department of Mathematics,Xiangnan University,Chenzhou 423000,China) |
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| Abstract: | In this paper,based on the time scales calculus theory and the Lyapunov functional method,we derived some sufficient conditions for the exponential syncheonization of a class of neural cetwork on time scales.The conditions possess highly important significance and are easily checked in pr actice by a simple algebraic method.Our rcsults unify and extend some continuous neural networks and their corresponding discrete analogues. |
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| Keywords: | exponential synchronization neural network time scales calculus delayed Lyapunov functions |
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