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Robust dissipativity and passivity analysis for discrete-time stochastic neural networks with time-varying delay
Complexity 21 (3):47-58 (2016)
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Fault-tolerant sampled-data mixed ℋ∞and passivity control of stochastic systems and its application.Maya Joby, R. Sakthivel, K. Mathiyalagan & S. Marshal Anthoni - 2016 - Complexity 21 (6):420-429.
Nonlinear system identification using quasi-arx rbfn models with a parameter-classified scheme.Lan Wang, Yu Cheng, Jinglu Hu, Jinling Liang & Abdullah M. Dobaie - 2017 - Complexity:1-12.
Robust state estimation for Markov jump genetic regulatory networks based on passivity theory.Li Lu, Bing He, Chuntao Man & Shun Wang - 2016 - Complexity 21 (5):214-223.
Nonlinear measure approach for the robust exponential stability analysis of interval inertial Cohen-Grossberg neural networks.Ruoxia Li, Jinde Cao, Ahmed Alsaedi, Bashir Ahmad, Fuad E. Alsaadi & Tasawar Hayat - 2016 - Complexity 21 (S2):459-469.
Nonfragile passivity and passification of nonlinear singular networked control systems with randomly occurring controller gain fluctuation.Aichuan Li & Bin Liu - 2016 - Complexity 21 (S1):200-210.
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.
Pinning sampled-data synchronization of complex dynamical networks with Markovian jumping and mixed delays using multiple integral approach.K. Sivaranjani & R. Rakkiyappan - 2016 - Complexity 21 (S1):622-632.
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