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Cluster synchronization between uncertain networks with different dynamics

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Listed:
  • Lü, Ling
  • Li, Chengren
  • Bai, Suyuan
  • Gao, Liyu
  • Ge, Lianjun
  • Han, Changhui

Abstract

We propose a new technique for the cluster synchronization between uncertain networks with different dynamics. Based on the Lyapunov theorem and Lipschitz condition, the network controllers and the identification laws of uncertain parameters are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain parameters. Particularly in our work, the dynamics of nodes in different clusters can be different. And there are not any limitations for the division of the clusters, the number of nodes in each cluster and the connections between nodes.

Suggested Citation

  • Lü, Ling & Li, Chengren & Bai, Suyuan & Gao, Liyu & Ge, Lianjun & Han, Changhui, 2017. "Cluster synchronization between uncertain networks with different dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 429-437.
    • Handle: RePEc:eee:phsmap:v:469:y:2017:i:c:p:429-437
    DOI: 10.1016/j.physa.2016.11.093
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    References listed on IDEAS

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    1. Zhou, Guangye & Li, Chengren & Li, Tingting & Yang, Yi & Wang, Chen & He, Fangjun & Sun, Jingchang, 2016. "Outer synchronization investigation between WS and NW small-world networks with different node numbers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 506-513.
    2. Li, Wenlin & Li, Chong & Song, Heshan, 2016. "Synchronization between uncertain nonidentical networks with quantum chaotic behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 270-277.
    3. Li, Wenlin & Li, Chong & Song, Heshan, 2016. "Synchronization transmission of target signal within the coupling network with quantum chaos effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 579-585.
    4. Lü, Ling & Chen, Liansong & Bai, Suyuan & Li, Gang, 2016. "A new synchronization tracking technique for uncertain discrete network with spatiotemporal chaos behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 314-325.
    5. Sakthivel, R. & Anbuvithya, R. & Mathiyalagan, K. & Ma, Yong-Ki & Prakash, P., 2016. "Reliable anti-synchronization conditions for BAM memristive neural networks with different memductance functions," Applied Mathematics and Computation, Elsevier, vol. 275(C), pages 213-228.
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    Cited by:

    1. Liu, Lingfeng & Miao, Suoxia, 2018. "Outer synchronization between delayed coupling networks with different dynamics and uncertain parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 890-901.
    2. Li, Chengren & Lü, Ling & Li, Gang & Zhao, Guannan & Gao, Liyu & Ge, Lianjun & Han, Changhui, 2019. "Cluster synchronization in uncertain network with nonidentical nodes based on adaptive pinning control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 742-749.
    3. Fu, Chenbo & Wang, Jinbao & Xiang, Yun & Wu, Zhefu & Yu, Li & Xuan, Qi, 2017. "Pinning control of clustered complex networks with different size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 184-192.
    4. Li, Chengren & Lü, Ling & Chen, Liansong & Hong, Yixuan & Zhou, Shuang & Yang, Yiming, 2018. "Cluster synchronization transmission of different external signals in discrete uncertain network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 238-247.

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