A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
Volume 13
Issue 9
IEEE/CAA Journal of Automatica Sinica
| Citation: | Y. Zheng and H.-T. Zhang, “Reconstructing community-bridge networks from heterogeneous and outlier-contaminated datasets,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 9, pp. 2181–2183, Sep. 2026. doi: 10.1109/JAS.2026.125771
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Q.-G. Wang and L. Zhang, “System identification in the network era: A survey of data issues and innovative approaches,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 7, pp. 1305−1319, 2025. doi: 10.1109/JAS.2024.125109
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M. Dimovska and D. Materassi, “An efficient network reconstruction method and applications,” IFAC-Pap., vol. 54, no. 7, pp. 49−54, 2021.
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I. Topal and D. Eroglu, “Reconstructing network dynamics of coupled discrete chaotic units from data,” Phys. Rev. Lett., vol. 130, no. 11, Art. no. 117401, 2023. doi: 10.1103/PhysRevLett.130.117401
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Z. Yue, J. Thunberg, W. Pan, L. Ljung, and J. Gonçalves, “Dynamic network reconstruction from heterogeneous datasets,” Automatica, vol. 123, Art. no. 109339, 2021. doi: 10.1016/j.automatica.2020.109339
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Y. Zheng, H.-T. Zhang, Z. Yue, and J. Wang, “Sparse Bayesian learning for switching network identification,” IEEE Trans. Cybern., vol. 54, no. 12, pp. 7642−7655, 2024. doi: 10.1109/TCYB.2024.3440933
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