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变时滞神经网络指数稳定性条件(
)
《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]
- 卷:
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第30卷
- 期数:
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2007年02期
- 页码:
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6-10
- 栏目:
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数学
- 出版日期:
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2007-06-30
文章信息/Info
- Title:
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Global Exponential Stability of Delayed Neural Networks
- 作者:
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蒋秋浩1; 2 ; 曹进德2
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(1. 中国药科大学数学系,江苏南京210009)
(2. 东南大学数学系,江苏南京210096)
- Author(s):
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Jiang Qiuhao1; 2; Cao Jinde2
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1.Department of Mathematics,China Pharmaceutical University,Nanjing 210009,China
2. Department ofMathematics, Southeast University, Nanjing 210096, China
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- 关键词:
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- Keywords:
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- 分类号:
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O175;O177
- 摘要:
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基于时滞细胞神经网络(DCNNs)在图像处理等领域的广泛应用,有关它的研究引起了越来越多学者和专家的关注.早期DCNNs稳定性的结果大多由网络权矩阵的分量构成的代数不等式来表示.运用Lyapunov-Krasovsk ii泛函的方法,研究了DCNNs的指数稳定性,所得充分条件以矩阵的(半)正定形式出现,在实际应用中更加便于验证.与文献中的结果相比较,所得判据适用范围更广.
- Abstract:
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In recent years, the study of cellular neural networks with delay (DCNNs) draws the attention of more and more specialists due to its extensive app lication in the fields of image p rocessing etc. The ear ly results on stability of DCNNs are usually rep resented by the elements ofweightmatrices of the network. In this paper, by emp loying the Lyapunov-Krasovskiimethod, global exponential stability of DCNNs is in vestigated, and sufficient conditions are obtained in the form ofmatrixwith ( semi-positive) positive defi niteness, and they are easier to be checked in p ractice. Compared to the earlier criteria, our results have more extensive app lications.
更新日期/Last Update:
2013-05-05