A Novel Condition for Robust Stability of Delayed Neural Networks

被引：0

作者：

Ozcan, Neyir ^{[1
]}

Yucel, Eylem ^{[2
]}

Arik, Sabri ^{[2
]}

机构：

[1] Uludag Univ, Dept Elect & Elect Engn, Bursa, Turkey

[2] Istanbul Univ, Dept Comp Engn, Istanbul, Turkey

来源：

NEURAL INFORMATION PROCESSING, PT III | 2015年 / 9491卷

关键词：

Neural networks; Lyapunov functionals; Stability analysis; TIME-VARYING DELAYS; EXPONENTIAL STABILITY; CRITERIA; MATRICES;

D O I：

10.1007/978-3-319-26555-1_31

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a novel sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of delayed neural networks by using the Homomorphic mapping and the Lyapunov stability theorems. An important feature of the obtained result is its low computational complexity as the reported result can be verified by checking some well-known properties of some certain classes of matrices, which simplify the verification of the derived result.

引用

页码：273 / 280

页数：8

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