Autowave principles for parallel image processing
Selcted papers from a meeting on Waves and pattern in chemical and biological media
Parameter-dependent robust stability of uncertain time-delay systems
Journal of Computational and Applied Mathematics
Globally exponential synchronization and synchronizability for general dynamical networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Exponential stability on stochastic neural networks with discrete interval and distributed delays
IEEE Transactions on Neural Networks
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
Pattern recognition via synchronization in phase-locked loop neural networks
IEEE Transactions on Neural Networks
Robust Synchronization of an Array of Coupled Stochastic Discrete-Time 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"~ synchronization control problem is investigated for a class of dynamical networks with randomly varying nonlinearities. The time varying nonlinearities of each node are modelled to be randomly switched between two different nonlinear functions by utilizing a Bernoulli distributed variable sequence specified by a randomly varying conditional probability distribution. A probability-dependent gain scheduling method is adopted to handle the time varying characteristic of the switching probability. Attention is focused on the design of a sequence of gain-scheduled controllers such that the controlled networks are exponentially mean-square stable and the H"~ synchronization performance is achieved in the simultaneous presence of randomly varying nonlinearities and external energy bounded disturbances. Except for constant gains, the desired controllers are also composed of time varying parameters, i.e., the time varying switching probability and therefore less conservatism will be resulted comparing with traditional controllers. In virtue of semi-definite programming method, controller parameters are derived in terms of the solutions to a series of linear matrix inequalities (LMIs) that can be easily solved by the Matlab toolboxes. Finally, a simulation example is exploited to illustrate the effectiveness of the proposed control strategy.