Stability of Time-Delay Systems
Stability of Time-Delay Systems
Linear hybrid systems with time-varying delays: H∞ stabilisation schemes
International Journal of Systems, Control and Communications
Complex dynamics and stability of Hopfield neural networks with delays
International Journal of Systems, Control and Communications
New Delay-Dependent Exponential Stability for Neural Networks With Time Delay
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Exponential Stability Analysis for Neural Networks With Time-Varying Delay
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Network-based robust H∞ control of systems with uncertainty
Automatica (Journal of IFAC)
Global stability for cellular neural networks with time delay
IEEE Transactions on Neural Networks
State estimation for delayed neural networks
IEEE Transactions on Neural Networks
New Delay-Dependent Stability Criteria for Neural Networks With Time-Varying Delay
IEEE Transactions on Neural Networks
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The problem of designing a state estimator having a global exponential convergence for a class of delayed neural networks of neutral-type is investigated in this paper. The time-delay pattern is a bounded differentiable time-varying function. The activation functions are globally Lipschitz. A linear estimator of Luenberger-type is developed and by properly constructing a new Lyapunov-Krasovskii functional coupled with the integral inequality, the global exponential stability conditions of the error system are derived. The unknown gain matrix is determined by solving a delay-dependent linear matrix inequality. The developed results are shown to be less conservative than previous published ones in the literature, which is illustrated by a representative numerical example.