Robust control of a class of uncertain nonlinear systems
Systems & Control Letters
Neural Networks for Optimization and Signal Processing
Neural Networks for Optimization and Signal Processing
Filtering for uncertain 2-D discrete systems with state delays
Signal Processing
Delay-dependent robust stability criteria for uncertain systems with interval time-varying delay
Journal of Computational and Applied Mathematics
Fuzzy filter design for itô stochastic systems with application to sensor fault detection
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Circuits and Systems Part I: Regular Papers
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Stabilization for T-S model based uncertain stochastic systems
Information Sciences: an International Journal
Global Synchronization in an Array of Delayed Neural Networks With Hybrid Coupling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Technical Communique: Delay-dependent criteria for robust stability of time-varying delay systems
Automatica (Journal of IFAC)
Hopfield neural networks for affine invariant matching
IEEE Transactions on Neural Networks
Markovian architectural bias of recurrent neural networks
IEEE Transactions on Neural Networks
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This paper addresses the problem of robust H"~ filter design for a class of stochastic Markovian jump Hopfield neural networks with mode-dependent time-varying delays and norm-bounded parameter uncertainties. The purpose is to design a mode-dependent linear filtering which ensures that, for all admissible uncertainties, the filtering error system is not only stochastically asymptotically stable in the large, but also satisfies a prescribed H"~-norm level. Some novel mode-dependent and delay-dependent sufficient conditions for the solvability of this problem are obtained. The desired filter can be constructed by solving a set of strict linear matrix inequalities. A numerical example is provided to illustrate the effectiveness of the proposed method.