Frustration, stability, and delay-induced oscillations in a neural network model
SIAM Journal on Applied Mathematics
Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
Stability analysis of dynamical neural networks
IEEE Transactions on Neural Networks
Stability analysis for neural dynamics with time-varying delays
IEEE Transactions on Neural Networks
A note on convergence under dynamical thresholds with delays
IEEE Transactions on Neural Networks
Global Asymptotic Stability Analysis of Neural Networks with Time-Varying Delays
Neural Processing Letters
Modeling and prediction with a class of time delay dynamic neural networks
Applied Soft Computing
Multiple almost periodic solutions in nonautonomous delayed neural networks
Neural Computation
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
ISTASC'08 Proceedings of the 8th conference on Systems theory and scientific computation
Global exponential stability of impulsive high-order Hopfield type neural networks with delays
Computers & Mathematics with Applications
Exponential Stability of Impulsive Hopfield Neural Networks with Time Delays
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Global Asymptotic Stability of Cohen-Grossberg Neural Networks with Multiple Discrete Delays
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Globally exponential stability of a class of impulsive neural networks with variable delays
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Globally Exponential Stability for Delayed Neural Networks Under Impulsive Control
Neural Processing Letters
A novel approach to exponential stability of nonlinear systems with time-varying delays
Journal of Computational and Applied Mathematics
Stability of nonautonomous recurrent neural networks with time-varying delays
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
New results for global exponential stability of delayed cohen-grossberg neural networks
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Universal approach to study delayed dynamical systems
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
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The stability of neural networks is a prerequisite for successful applications of the networks as either associative memories or optimization solvers. Because the integration and communication delays are ubiquitous, the stability of neural networks with delays has received extensive attention. However, the approach used in the previous investigation is mainly based on Liapunov's direct method. Since the construction of Liapunov function is very skilful, there is little compatibility among the existing results. In this paper, we develop a new approach to stability analysis of Hopfield-type neural networks with time-varying delays by defining two novel quantities of nonlinear function similar to the matrix norm and the matrix measure, respectively. With the new approach, we present sufficient conditions of the stabliity, which are either the generalization of those existing or new. The developed approach may be also applied for any general system with time delays rather than Hopfield-type neural networks.