Stability of Time-Delay Systems
Stability of Time-Delay Systems
A new delay system approach to network-based control
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
State estimation for delayed neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Delay-dependent state estimation for delayed neural networks
IEEE Transactions on Neural Networks
Global -Stability of Delayed Neural Networks With Unbounded Time-Varying Delays
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Computers & Mathematics with Applications
Associative Learning of Integrate-and-Fire Neurons with Memristor-Based Synapses
Neural Processing Letters
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In this paper, the state estimation problem is investigated for neural networks with discrete interval time-varying delays and distributed time-varying delays as well as general activation functions. By constructing appropriate Lyapunov-Krasovskii functional and employing Newton-Leibniz formulation and linear matrix inequality (LMI) technique, a delay-interval-dependent condition is developed to estimate the neuron state with some available output measurements such that the error-state system is global asymptotically stable. Two examples are given to show the effectiveness and decreased conservatism of the proposed criterion in comparison with some existing results. It is noteworthy that the traditional assumptions on the differentiability of the time-varying delays and the boundedness of their derivative are removed.