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State estimation for complex networks with randomly varying nonlinearities and sensor failures
Complexity 21 (S2):507-517 (2016)
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References found in this work
State estimation of memristor‐based recurrent neural networks with time‐varying delays based on passivity theory.R. Rakkiyappan, A. Chandrasekar, S. Laksmanan & Ju H. Park - 2014 - Complexity 19 (4):32-43.
Exponential state estimator design for discrete-time neural networks with discrete and distributed time-varying delays.Qihui Duan, Ju H. Park & Zheng-Guang Wu - 2014 - Complexity 20 (1):38-48.
Cluster synchronization for T-S fuzzy complex networks using pinning control with probabilistic time-varying delays.Rajan Rakkiyappan & Natarajan Sakthivel - 2016 - Complexity 21 (1):59-77.
Non-fragile synchronization control for complex networks with additive time-varying delays.Natarajan Sakthivel, Rajan Rakkiyappan & Ju H. Park - 2016 - Complexity 21 (1):296-321.
Classification of Structural Complexity for Mine Ventilation Networks.Lian-Jiang Wei, Fu-Bao Zhou, Jian-Wei Cheng, Xin-Rong Luo & Xiao-Lin Li - 2016 - Complexity 21 (1):21-34.
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