Stability of Time-Delay Systems
Stability of Time-Delay Systems
Global robust stability of neural networks with time varying delays
Journal of Computational and Applied Mathematics
Global stability for cellular neural networks with time delay
IEEE Transactions on Neural Networks
An analysis of global asymptotic stability of delayed cellular neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Mathematics and Computers in Simulation
Novel robust stability criteria for stochastic hopfield neural network with time-varying delays
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
International Journal of Innovative Computing and Applications
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Using the Lyapunov-Krasovskii functional method and the linear matrix inequality (LMI) technique, this paper is concerned with the robust stability of generalized neural networks with multiple discrete delays and multiple distributed delays. The global stability of the equilibrium point is proved under mild conditions, where the activation function is neither differentiable nor strictly monotone. For the considered system, a novel robust stability criterion of the system is derived, which can be easily solved by efficient convex optimization algorithms. And two numerical examples are given to justify the obtained results.