Brief paper: Robust filtering with stochastic nonlinearities and multiple missing measurements
Automatica (Journal of IFAC)
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Globally exponential synchronization and synchronizability for general dynamical networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Exponential synchronization of hybrid coupled networks with delayed coupling
IEEE Transactions on Neural Networks
IEEE Transactions on Fuzzy Systems
Robust H∞ finite-horizon filtering with randomly occurred nonlinearities and quantization effects
Automatica (Journal of IFAC)
Robust H/sub /spl infin// filtering for stochastic time-delay systems with missing measurements
IEEE Transactions on Signal Processing
Synchronization and State Estimation for Discrete-Time Complex Networks With Distributed Delays
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
State estimation for delayed neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements
Automatica (Journal of IFAC)
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In this paper, the H"~ state estimation problem is investigated for a class of discrete-time complex networks with randomly occurring phenomena. The proposed randomly occurring phenomena include both probabilistic missing measurements and randomly occurring coupling delays which are described by two random variable sequences satisfying individual probability distributions, respectively. Rather than the common Lipschitz-type function, a more general sector-like nonlinear function is employed to characterize the nonlinearities in the networks. The purpose of the addressed H"~ state estimation problem is to design a state estimator such that, for all admissible nonlinear disturbances, missing measurements as well as coupling delays, the dynamics of the augmented systems is guaranteed to be exponentially mean-square stable and attenuated to a given H"~ performance level. By constructing a novel Lyapunov-Krasovskii functional and utilizing convex optimization method as well as Kronecker product, we derive the sufficient conditions under which the desired state estimator exists. An illustrative example is exploited to show the effectiveness of the proposed state estimation scheme.