Stability Criteria with Less Variables for Neural Networks with Time-Varying Delay

Authors:
Tao Li;Xiaoling Ye;Yingchao Zhang
Affiliations:
Department of Information and Communication, Nanjing University of Information Science and Technology, Nanjing, China 210044;Department of Information and Communication, Nanjing University of Information Science and Technology, Nanjing, China 210044;Department of Information and Communication, Nanjing University of Information Science and Technology, Nanjing, China 210044
Venue:
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Year:
2008

Citing 10
Cited 0

Neural Networks for Optimization and Signal Processing

Neural Networks for Optimization and Signal Processing
Delay-dependent exponential stability analysis of delayed neural networks: an LMI approach

Neural Networks
Global exponential stability of generalized recurrent neural networks with discrete and distributed delays

Neural Networks
Letters: Robust stability for neural networks with time-varying delays and linear fractional uncertainties

Neurocomputing
Letters: Further result on asymptotic stability criterion of neural networks with time-varying delays

Neurocomputing
Improved conditions for global exponential stability of recurrent neural networks with time-varying delays

IEEE Transactions on Neural Networks
Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays

IEEE Transactions on Neural Networks
New Delay-Dependent Stability Criteria for Neural Networks With Time-Varying Delay

IEEE Transactions on Neural Networks
Stability and Hopf Bifurcation in a Simplified BAM Neural Network With Two Time Delays

IEEE Transactions on Neural Networks
Global Asymptotic Stability of Delayed Cellular Neural Networks

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, new delay-dependent stability criterion for neural networks is derived by using a simple integral inequality. The result is in terms of linear matrix inequalities and turn out to be equivalent to the existing result but include the least number of variables. This implies that some redundant variables in the existing stability criterion can be removed while maintaining the efficiency of the stability conditions. With the present stability condition, the computational burden is largely reduced. A numerical example is given to verify the effectiveness of the proposed criterion.