Synchronization analysis of linearly coupled networks of discrete time systems

By Wenlian Lu, Tianping Chen. 2004

149 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/9725f06515192c500c2518f367fd7f6addd0e2b4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Guanrong Chen
2. Zidong Wang
3. Xiaohui Liu
4. Jinling Liang
5. Yurong Liu
6. Z. Duan
7. Wenwu Yu
8. Zhongkui Li

In Statistical and Nonlinear Physics

1. Zidong Wang
2. Guanrong Chen
3. Xiwei Liu
4. Tianping Chen
5. Xiaohui Liu
6. Jinling Liang
7. Yurong Liu
8. Z. Duan

Citations in the corpus

• Consensus of Multiagent Systems and Synchronization of Complex Networks: A Unified Viewpoint (2016, background): “been given in [2], [3], and the results obtained in [1] can be easily derived by those given in [2], [3].”
• Synchronization and State Estimation for Discrete-Time Complex Networks With Distributed Delays (2008, unknown): “In [24] and [25], the synchronization problem has been studied for an array of discrete-time coupled complex networks in a systematic way and a series of results was obtained by using innovative manifold/graph approaches.”
• Synchronization of Complex Networks via Aperiodically Intermittent Pinning Control (2015, background): “It includes impulsive control, sample-data control [16], node-to-node pinning control [17]–[20], fast-switching strategy [21], edge snapping pinning control ([22], [23]), and the event-triggered scheduling algorithm ([24]–[31]).”
• Stability and Synchronization of Discrete-Time Markovian Jumping Neural Networks With Mixed Mode-Dependent Time Delays (2009, background): “In [25]–[27], Lu and Chen investigated the synchronization problem for an array of discrete-time coupled complex networks in a systematic way and obtained a series of elegant results by using innovative manifold/graph approaches.”