Technical communique: Observer-based H∞ fuzzy control design for T-S fuzzy systems with state delays
Automatica (Journal of IFAC)
IEEE Transactions on Neural Networks
Novel weighting-delay-based stability criteria for recurrent neural networks with time-varying delay
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Robust state estimation for neural networks with discontinuous activations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Input-to-state stabilization of dynamic neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Online stabilization of block-diagonal recurrent neural networks
IEEE Transactions on Neural Networks
State estimation for delayed neural networks
IEEE Transactions on Neural Networks
Delay-dependent state estimation for delayed neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Stability Analysis and the Stabilization of a Class of Discrete-Time Dynamic Neural Networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Robust State Estimation for Uncertain Neural Networks With Time-Varying Delay
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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This paper is concerned with the stabilization problem of delayed recurrent neural networks. As the states of neurons are usually difficult to be fully measured, a state estimation based approach is presented. First, a sufficient condition is derived such that the augmented system under consideration is globally exponentially stable. Then, by employing a decoupling technique, the gain matrices of the controller and state estimator are achieved by solving some linear matrix inequalities. Finally, a delayed neural network with chaotic behaviors is exploited to demonstrate the applicability of the developed result.