Stability and synchronization of directed complex dynamical networks with random packet loss: the continuous-time case and the discrete-time case

2012 ◽  
Vol 41 (12) ◽  
pp. 1272-1289 ◽  
Author(s):  
Meng Yang ◽  
Yan-Wu Wang ◽  
Jing-Wen Yi ◽  
Yuehua Huang
Keyword(s):  
Discrete Time ◽  
Packet Loss ◽  
Continuous Time ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Random Packet Loss ◽  
Discrete Time Case

scholarly journals Pinning Synchronization of Nonlinearly Coupled Complex Dynamical Networks on Time Scales

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fang-Di Kong
Keyword(s):  
Time Scales ◽  
Discrete Time ◽  
Control Strategy ◽  
Continuous Time ◽  
General Framework ◽  
Pinning Control ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Numerical Examples ◽  
Synchronization Problem

In this paper, we study the synchronization problem for nonlinearly coupled complex dynamical networks on time scales. To achieve synchronization for nonlinearly coupled complex dynamical networks on time scales, a pinning control strategy is designed. Some pinning synchronization criteria are established for nonlinearly coupled complex dynamical networks on time scales, which guarantee the whole network can be pinned to some desired state. The model investigated in this paper generalizes the continuous-time and discrete-time nonlinearly coupled complex dynamical networks to a unique and general framework. Moreover, two numerical examples are given for illustration and verification of the obtained results.

scholarly journals On the total reward variance for continuous-time Markov reward chains

2006 ◽  
Vol 43 (04) ◽  
pp. 1044-1052 ◽  
Author(s):  
Nico M. Van Dijk ◽  
Karel Sladký
Keyword(s):  
Growth Rate ◽  
Discrete Time ◽  
Continuous Time ◽  
Asymptotically Linear ◽  
State Spaces ◽  
Total Reward ◽  
Finite State ◽  
Markov Reward ◽  
Discrete Time Case

As an extension of the discrete-time case, this note investigates the variance of the total cumulative reward for continuous-time Markov reward chains with finite state spaces. The results correspond to discrete-time results. In particular, the variance growth rate is shown to be asymptotically linear in time. Expressions are provided to compute this growth rate.

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