Global Exponential Stability for Impulsive BAM Neural Networks with Distributed Delays on Time Scales

被引：29
|
作者：
Li, Yongkun [1 ]
Gao, Shan [1 ]
机构：
[1] Yunnan Univ, Dept Math, Kunming 650091, Yunnan, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2010年 / 31卷 / 01期
关键词：
Global exponential stability; BAM neural network; Impulsive; Distributed delays; Time scale; Topological degree theory; BIDIRECTIONAL ASSOCIATIVE MEMORY; ASYMPTOTIC STABILITY; PERIODIC-SOLUTION; DYNAMIC EQUATIONS; EXISTENCE;
D O I：
10.1007/s11063-009-9127-z
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, by utilizing the time scale calculus theory, topological degree theory and Holder's inequality on time scales, we analyze a class of impulsive BAM neural networks with distributed delays on time scales. Some sufficient conditions are obtained to ensure the existence, uniqueness and the global exponential stability of the equilibrium point. Finally, an example is provided to demonstrate the effectiveness of the results.
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页码：65 / 91
页数：27
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