Stability of Time-Delay Systems
Stability of Time-Delay Systems
Delay-dependent H∞ and generalized H2 filtering for delayed neural networks
IEEE Transactions on Circuits and Systems Part I: Regular Papers
New Lyapunov-Krasovskii functionals for global asymptotic stability of delayed neural networks
IEEE Transactions on Neural Networks
A scaling parameter approach to delay-dependent state estimation of delayed neural networks
IEEE Transactions on Circuits and Systems II: Express Briefs
Robust state estimation for neural networks with discontinuous activations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Convergence of a Subclass of Cohen–Grossberg Neural Networks via the Łojasiewicz Inequality
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
State estimation for delayed neural networks
IEEE Transactions on Neural Networks
Delay-dependent state estimation for delayed neural networks
IEEE Transactions on Neural Networks
A New Criterion of Delay-Dependent Asymptotic Stability for Hopfield Neural Networks With Time Delay
IEEE Transactions on Neural Networks
Robust State Estimation for Uncertain Neural Networks With Time-Varying Delay
IEEE Transactions on Neural Networks
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This paper is concerned with studying the robust H∞ filter design problem for a class of recurrent neural networks with timevarying delay. A delay-dependent criterion involving a scaling parameter is established under which the resulting filtering error system is globally asymptotically stable with a guaranteed performance in the H∞ sense. The purpose of the introduction of the scaling parameter lies in that the developed result can be efficiently applied to the neural networks with complex dynamic behaviors, which is illustrated by an example.