This paper investigates event-triggered synchronization for complex networks with Markovian jumping parameters.Nonlinear dynamics with Markovian jumping parameters is considered for each node in a complex network. By ...This paper investigates event-triggered synchronization for complex networks with Markovian jumping parameters.Nonlinear dynamics with Markovian jumping parameters is considered for each node in a complex network. By utilizing the proposed event-triggered strategy, and based on the Lyapunov functional method and linear matrix inequality technology,some sufficient conditions for synchronization of complex networks are derived whether the transition rate matrix for the Markov process is completely known or not. Finally, a numerical example is presented to illustrate the effectiveness of the proposed theoretical results.展开更多
This article discusses the synchronization problem of singular neutral complex dynamical networks(SNCDN)with distributed delay and Markovian jump parameters via pinning control.Pinning control strategies are designed ...This article discusses the synchronization problem of singular neutral complex dynamical networks(SNCDN)with distributed delay and Markovian jump parameters via pinning control.Pinning control strategies are designed to make the singular neutral complex networks synchronized.Some delay-dependent synchronization criteria are derived in the form of linear matrix inequalities based on a modified Lyapunov-Krasovskii functional approach.By applying the Lyapunov stability theory,Jensen's inequality,Schur complement,and linear matrix inequality technique,some new delay-dependent conditions are derived to guarantee the stability of the system.Finally,numerical examples are presented to illustrate the effectiveness of the obtained results.展开更多
We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks （MJFCNNs） with discrete, unbounded distributed delays, and the Wiener process based on sampled-d...We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks （MJFCNNs） with discrete, unbounded distributed delays, and the Wiener process based on sampled-data control using the linear matrix inequality （LMI） approach. The Lyapunov–Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous. Restrictions （e.g., time derivative is smaller than one） are removed to obtain a proposed sampled-data controller. Finally, a numerical example is provided to demonstrate the reliability of the derived results.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.11202084)
文摘This paper investigates event-triggered synchronization for complex networks with Markovian jumping parameters.Nonlinear dynamics with Markovian jumping parameters is considered for each node in a complex network. By utilizing the proposed event-triggered strategy, and based on the Lyapunov functional method and linear matrix inequality technology,some sufficient conditions for synchronization of complex networks are derived whether the transition rate matrix for the Markov process is completely known or not. Finally, a numerical example is presented to illustrate the effectiveness of the proposed theoretical results.
基金The work of author was supported by NBHM grant.2/48(5)/2016/NBHMR.P)/-R-D II/14088。
文摘This article discusses the synchronization problem of singular neutral complex dynamical networks(SNCDN)with distributed delay and Markovian jump parameters via pinning control.Pinning control strategies are designed to make the singular neutral complex networks synchronized.Some delay-dependent synchronization criteria are derived in the form of linear matrix inequalities based on a modified Lyapunov-Krasovskii functional approach.By applying the Lyapunov stability theory,Jensen's inequality,Schur complement,and linear matrix inequality technique,some new delay-dependent conditions are derived to guarantee the stability of the system.Finally,numerical examples are presented to illustrate the effectiveness of the obtained results.
基金the Ministry of Science and Technology of India(Grant No.DST/Inspire Fellowship/2010/[293]/dt.18/03/2011)
文摘We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks （MJFCNNs） with discrete, unbounded distributed delays, and the Wiener process based on sampled-data control using the linear matrix inequality （LMI） approach. The Lyapunov–Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous. Restrictions （e.g., time derivative is smaller than one） are removed to obtain a proposed sampled-data controller. Finally, a numerical example is provided to demonstrate the reliability of the derived results.
