Novel delay-dependent exponential stability analysis for a class of delayed neural networks

Authors:
Zhiqiang Zuo;Yijing Wang
Affiliations:
School of Electrical Engineering & Automation, Tianjin University, Tianjin, China;School of Electrical Engineering & Automation, Tianjin University, Tianjin, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

Citing 4
Cited 2

Delay-dependent exponential stability analysis of delayed neural networks: an LMI approach

Neural Networks
Necessary and sufficient condition for absolute stability of normal neural networks

Neural Networks
An analysis of exponential stability of delayed neural networks with time varying delays

Neural Networks
Delay-dependent exponential stability for a class of neural networks with time delays

Journal of Computational and Applied Mathematics

Global Stability of Neural Networks with Time-Varying Delays

ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
A semi-free weighting matrices approach for neutral-type delayed neural networks

Journal of Computational and Applied Mathematics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper deals with the problem of exponential stability for a class of delayed neural networks described by nonlinear delay differential equations of neutral type. A less conservative exponential stability condition is derived based on a new Lyapunov-Krasovskii functional in term of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed methods.