Stability of Time-Delay Systems
Stability of Time-Delay Systems
Filtering for networked stochastic time-delay systems with sector nonlinearity
IEEE Transactions on Circuits and Systems II: Express Briefs
Almost sure exponential stability of recurrent neural networks with Markovian switching
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Automatica (Journal of IFAC)
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
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Technical communique: Reciprocally convex approach to stability of systems with time-varying delays
Automatica (Journal of IFAC)
Convergence of a Subclass of Cohen–Grossberg Neural Networks via the Łojasiewicz Inequality
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
Synchronization and State Estimation for Discrete-Time Complex Networks With Distributed Delays
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Markovian architectural bias of 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
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
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Delay-Dependent Stability Analysis for Switched Neural Networks With Time-Varying Delay
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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This paper is concerned with the problem of state estimation of recurrent neural networks with Markovian jumping parameters and mixed delays. A mode-dependent approach is proposed by constructing a novel Lyapunov functional, where some terms involving triple or quadruple integrals are taken into account. The advantage is that as many as possible of the Lyapunov matrices are chosen to be mode-dependent. Several design criteria are established under which the estimation error system is globally exponentially stable in the mean square sense. The gain matrices of the state estimator can be then found by solving a set of coupled linear matrix inequalities. It is shown in theory that better performance can be achieved by this approach. Furthermore, by introducing some scaling parameters, this approach is effectively employed to deal with the state estimation problem of the neural networks with complex dynamic behaviors, to which some existing results are not applicable.