A general model of linearly stochastically coupled identical connected neural networks with hybrid coupling is proposed, which is composed of constant coupling, coupling discrete time-varying delay and coupling distri...A general model of linearly stochastically coupled identical connected neural networks with hybrid coupling is proposed, which is composed of constant coupling, coupling discrete time-varying delay and coupling distributed time-varying delay. All the coupling terms are subjected to stochastic disturbances described in terms of Brownian motion, which reflects a more realistic dynamical behaviour of coupled systems in practice. Based on a simple adaptive feedback controller and stochastic stability theory, several sufficient criteria are presented to ensure the synchronization of linearly stochastically coupled complex networks with coupling mixed time-varying delays. Finally, numerical simulations illustrated by scale-free complex networks verify the effectiveness of the proposed controllers.展开更多
This paper is concerned with the problem of robust H ∞ control for structured uncertain stochastic neural networks with both discrete and distributed time varying delays.A sufficient condition is presented for the ex...This paper is concerned with the problem of robust H ∞ control for structured uncertain stochastic neural networks with both discrete and distributed time varying delays.A sufficient condition is presented for the existence of H ∞ control based on the Lyapunov stability theory.The stability criterion is described in terms of linear matrix inequalities (LMIs),which can be easily checked in practice.An example is provided to demonstrate the effectiveness of the proposed result.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No 60874113)
文摘A general model of linearly stochastically coupled identical connected neural networks with hybrid coupling is proposed, which is composed of constant coupling, coupling discrete time-varying delay and coupling distributed time-varying delay. All the coupling terms are subjected to stochastic disturbances described in terms of Brownian motion, which reflects a more realistic dynamical behaviour of coupled systems in practice. Based on a simple adaptive feedback controller and stochastic stability theory, several sufficient criteria are presented to ensure the synchronization of linearly stochastically coupled complex networks with coupling mixed time-varying delays. Finally, numerical simulations illustrated by scale-free complex networks verify the effectiveness of the proposed controllers.
基金Project is supported in part by the National Natural Science Foundation of China (Grant No 60474031)NCET (04-0383)+2 种基金the State Key Development Program for Basic Research of China (Grant No 2002cb312200-3)the Shanghai ‘Phosphor’ Foundation(Grant No 04QMH1405)Australia-China Special Fund for Scientific & Technological Cooperation
文摘This paper is concerned with the problem of robust H ∞ control for structured uncertain stochastic neural networks with both discrete and distributed time varying delays.A sufficient condition is presented for the existence of H ∞ control based on the Lyapunov stability theory.The stability criterion is described in terms of linear matrix inequalities (LMIs),which can be easily checked in practice.An example is provided to demonstrate the effectiveness of the proposed result.
