References
- An, B.-R., Liu, G.-P., & Tan, C. (2018). Group consensus control for networked multi-agent systems with communication delays. ISA Transactions, 76, 78–87. https://doi.org/https://doi.org/10.1016/j.isatra.2018.03.008
- Baran, L., & Rzysko, W. (2020). Application of a coarse-grained model for the design of complex supramolecular networks. Molecular Systems Design
Engineering, 5(2), 484–492. https://doi.org/https://doi.org/10.1039/C9ME00122K
- Bonello, J., Demarco, A., Farhat, I., Farrugia, L., & Sammut, C. V. (2020). Application of artificial neural networks for accurate determination of the complex permittivity of biological tissue. Sensors, 20(16), 1–18. https://doi.org/https://doi.org/10.3390/s20164640
- Bougofa, M., Bouafia, A., & Bellaouar, A. (2020). Availability assessment of complex systems under parameter uncertainty using dynamic evidential networks. International Journal of Performability Engineering, 16(4), 510–519. https://doi.org/https://doi.org/10.23940/ijpe.20.04.p2.510519
- Chen, D., Chen, W., Hu, J., & Liu, H. (2019). Variance-constrained filtering for discrete-time genetic regulatory networks with state delay and random measurement delay. International Journal of Systems Science, 50(2), 231–243. https://doi.org/https://doi.org/10.1080/00207721.2018.1542045
- Chen, W., Hu, J., Wu, Z., Yu, X., & Chen, D. (2020). Finite-time memory fault detection filter design for nonlinear discrete systems with deception attacks. International Journal of Systems Science, 51(8), 1464–1481. https://doi.org/https://doi.org/10.1080/00207721.2020.1765219
- Ding, R., Ujang, N., Bin Hamid, H., Abd Manan, M. S., Li, R., Albadareen, S. S. M., Nochian, A., & Wu, J. (2019). Application of complex networks theory in urban traffic network researches. Networks
Spatial Economics, 19(4), 1281–1317. https://doi.org/https://doi.org/10.1007/s11067-019-09466-5
- Hernandez-torres, J. E., Hernandez-gonzalez, S., Jimenez-garcia, J. A., & Figureoa-fernandez, V. (2020). Application of complex networks theory for transportation infrastructure analysis: celaya's city avenue network. Revista Eia, 17(33), 43–45. https://doi.org/https://doi.org/10.24050/reia.v17i33.1305
- Hu, J., Cui, Y., Lv, C., Chen, D., & Zhang, H. (2020). Robust adaptive sliding mode control for discrete singular systems with randomly occurring mixed time-delays under uncertain occurrence probabilities. International Journal of Systems Science, 51(6), 987–1006. https://doi.org/https://doi.org/10.1080/00207721.2020.1746439
- Hu, J., Liu, G.-P., Zhang, H., & Liu, H. (2020). On state estimation for nonlinear dynamical networks with random sensor delays and coupling strength under event-based communication mechanism. Information Sciences, 511, 265–283. https://doi.org/https://doi.org/10.1016/j.ins.2019.09.050
- Hu, J., Wang, Z., Alsaadi, F. E., & Hayat, T. (2017). Event-based filtering for time-varying nonlinear systems subject to multiple missing measurements with uncertain missing probabilities. Information Fusion, 38, 74–83. https://doi.org/https://doi.org/10.1016/j.inffus.2017.03.003
- Hu, J., Wang, Z., Chen, D., & Alsaadi, F. E. (2016). Estimation, filtering and fusion for networked systems with network-induced phenomena: new progress and prospects. Information Fusion, 31, 65–75. https://doi.org/https://doi.org/10.1016/j.inffus.2016.01.001
- Hu, J., Wang, Z., Liu, G.-P., Jia, C., & Williams, J. (2020). Event-triggered recursive state estimation for dynamical networks under randomly switching topologies and multiple missing measurements. Automatica, 115. Article No: 108908. doi:https://doi.org/10.1016/j.automatica.2020.108908
- Hu, J., Wang, Z., Liu, G.-P., & Zhang, H. (2020). Variance-constrained recursive state estimation for time-varying complex networks with quantized measurements and uncertain inner coupling. IEEE Transactions on Neural Networks and Learning Systems, 31(6), 1955–1967. https://doi.org/https://doi.org/10.1109/TNNLS.5962385
- Hu, J., Zhang, P., Kao, Y., Liu, H., & Chen, D. (2019). Sliding mode control for Markovian jump repeated scalar nonlinear systems with packet dropouts: The uncertain occurrence probabilities case. Applied Mathematics and Computation, 362. Article number: 124574. https://doi.org/https://doi.org/10.1016/j.amc.2019.124574
- Hu, J., Zhang, H., Yu, X., Liu, H., & Chen, D. (2019). Design of sliding-mode-based control for nonlinear systems with mixed-delays and packet losses under uncertain missing probability. IEEE Transactions on Systems, Man, and Cybernetics: Systems. doi:https://doi.org/10.1109/TSMC.2019.2919513
- Li, W., & J. Du, Y. J (2017). Recursive state estimation for complex networks with random coupling strength. Neurocomputing, 219, 1–8. https://doi.org/https://doi.org/10.1016/j.neucom.2016.08.095
- Li, W., Jia, Y., Du, J., & Fu, X. (2018). State estimation for nonlinearly coupled complex networks with application to multi-target tracking. Neurocomputing, 275, 1884–1892. https://doi.org/https://doi.org/10.1016/j.neucom.2017.10.012
- Liu, Y., Li, W., & Feng, J. (2018). Graph-theoretical method to the existence of stationary distribution of stochastic coupled systems. Journal of Dynamics and Differential Equations, 30(2), 667–685. https://doi.org/https://doi.org/10.1007/s10884-016-9566-y
- Locke, R., Kupis, S., Gehb, C. M., Platz, R., & Atamturktur, S. (2020). Applying uncertainty quantification to structural systems: parameter reduction for evaluating model complexity. Conference Proceedings of the Society for Experimental Mechanics Series, 3, 241–256. https://doi.org/https://doi.org/10.1007/978-3-030-12075-7
- Luo, Y., Deng, F., Ling, Z., & Cheng, Z. (2019). Local H∞ synchronization of uncertain complex networks via non-fragile state feedback control. Mathematics and Computers in Simulation, 155, 335–346. https://doi.org/https://doi.org/10.1016/j.matcom.2018.07.009
- Ma, L., Wang, Z., Han, Q.-L., & Liu, Y. (2018). Dissipative control for nonlinear Markovian jump systems with actuator failures and mixed time-delays. Automatica, 98, 358–362. https://doi.org/https://doi.org/10.1016/j.automatica.2018.09.028
- Ma, L., Wang, Z., Liu, Y., & Alsaadi, F. E. (2019). Distributed filtering for nonlinear time-delay systems over sensor networks subject to multiplicative link noises and switching topology. International Journal of Robust and Nonlinear Control, 29(10), 2941–2959. https://doi.org/https://doi.org/10.1002/rnc.v29.10
- Malinin, A., & Gales, M. (2018). Predictive uncertainty estimation via prior networks. Proceedings of the 32nd International Conference on Neural Information Processing Systems, December 2018, New York, United States, Pages 7047–7058.
- Mao, J., Sun, Y., Yi, X., Liu, H., & Ding, D. (2021). Recursive filtering of networked nonlinear systems: A survey. International Journal of Systems Science. doi:https://doi.org/10.1080/00207721.2020.1868615.
- Wang, L., An, M., Jia, L., & Qin, Y. (2019). Application of complex network principles to key station identification in railway network efficiency analysis. Journal of Advanced Transportation, 2019, 1–13. Article ID 1574136. https://doi.org/https://doi.org/10.1155/2019/1574136
- Wu, Y., & He, X. (2017). Secure consensus control for multi-agent systems with attacks and communication delays. IEEE/CAA Journal of Automatica Sinica, 4(1), 136–142. https://doi.org/https://doi.org/10.1109/JAS.2016.7510010
- Wu, Z.-G., Xu, Z., Shi, P., Chen, M. Z. Q., & Su, H. (2018). Nonfragile state estimation of quantized complex networks with switching topologies. IEEE Transactions on Neural Networks and Learning Systems, 29(10), 5111–5121. https://doi.org/https://doi.org/10.1109/TNNLS.2018.2790982
- Xia, J., Gao, S., Zhong, Y., Zhang, J., Gu, C., & Liu, Y. (2020). A novel fitting H∞ Kalman filter for nonlinear uncertain discrete-time systems based on fitting transformation. IEEE Access, 8, 10554–10568. https://doi.org/https://doi.org/10.1109/Access.6287639
- Xiong, Q., Lin, P., Ren, W., Yang, C., & Gui, W. (2018). Containment control for discrete-time multiagent systems with communication delays and switching topologies. IEEE Transactions on Cybernetics, 49(10), 3827–3830. https://doi.org/https://doi.org/10.1109/TCYB.6221036
- Xue, B., Wang, R., & Fei, S. (2020). Time-varying H∞ filtering for discrete-time switched systems with admissible edge-dependent average dwell time. Transactions of the Institute of Measurement and Control, 42(14), 2719–2732. https://doi.org/https://doi.org/10.1177/0142331220928889
- Zhao, J. (2018). Dynamic state estimation with model uncertainties using H∞ extended Kalman filter. IEEE Transactions on Power Systems, 33(1), 1099–1100. https://doi.org/https://doi.org/10.1109/TPWRS.2017.2688131
- Zhao, J., & Mili, L. (2019). A theoretical framework of robust H∞ unscented Kalman filter and its application to power system dynamic state estimation. IEEE Transactions on Signal Processing, 67(10), 2734–2746. https://doi.org/https://doi.org/10.1109/TSP.78
- Zou, L., Wang, Z., Dong, H., & Han, Q.-L. (2020). Moving horizon estimation with multi-rate measurements and correlated noises. International Journal of Robust and Nonlinear Control, 30(17), 7429–7445. https://doi.org/https://doi.org/10.1002/rnc.v30.17
- Zou, L., Wang, Z., Han, Q.-L., & Zhou, D. (2019). Moving horizon estimation of networked nonlinear systems with random access protocol. IEEE Transactions on Systems, Man, and Cybernetics-Systems. in press. doi:https://doi.org/10.1109/TSMC.2019.2918002
- Zou, L., Wang, Z., Hu, J., & Zhou, D.-H. (2020). Moving horizon estimation with unknown inputs under dynamic quantization effects. IEEE Transactions on Automatic Control, 65(12), 5368–5375. https://doi.org/https://doi.org/10.1109/TAC.9
- Zou, L., Wen, T., Wang, Z., Chen, L., & Roberts, C. (2019). State estimation for communication-based train control systems with CSMA protocol. IEEE Transactions on Intelligent Transportation Systems, 20(3), 843–854. https://doi.org/https://doi.org/10.1109/TITS.2018.2835655