Event-based passification of delayed memristive neural networks
Tài liệu tham khảo
Shen, 2018, Finite-time event-triggered H∞ control for T-S fuzzy Markov jump systems, IEEE Trans. Fuzzy Syst., 26, 3122, 10.1109/TFUZZ.2017.2788891
Xu, 2014, On antiperiodic solutions for Cohen-Grossberg shunting inhibitory neural networks with time-varying delays and impulses, Neural Comput., 26, 2328, 10.1162/NECO_a_00642
Chua, 1971, Memristor-the missing circuit element, IEEE Trans. Circuit Theory, 18, 507, 10.1109/TCT.1971.1083337
Tour, 2008, Electronics: the fourth element, Nature, 453, 42, 10.1038/453042a
Guo, 2018, Finite-time synchronization of inertial memristive neural networks with time delay via delay-dependent control, Neurocomputing, 293, 100, 10.1016/j.neucom.2018.03.004
Lin, 2015, Synchronization of fuzzy modeling chaotic time delay memristor-based chua’s circuits with application to secure communication, Int. J. Fuzzy Syst., 17, 206, 10.1007/s40815-015-0024-5
Wen, 2019, Memristor-based design of sparse compact convolutional neural networks, IEEE Trans. Network Sci. Eng., 99, 1
Cao, 2019, Synchronization of memristive neural networks with leakage delay and parameters mismatch via event-triggered control, Neural Networks, 119, 178, 10.1016/j.neunet.2019.08.011
Wang, 2020, Event-triggered synchronization of multiple memristive neural networks with cyber-physical attacks, Inf. Sci., 518, 361, 10.1016/j.ins.2020.01.022
C. Xu, P. Li, J.N. Pang, Yicheng, Exponential stability of almost periodic solutions for memristor-based neural networks with distributed leakage delays 28(12) (2016) 2726–2756.
Guo, 2015, Global exponential synchronization of two memristor-based recurrent neural networks with time delays via static or dynamic coupling, IEEE Trans. Syst. Man Cybern. Syst., 45, 235, 10.1109/TSMC.2014.2343911
A. Wu, Z. Zeng, Exponential passivity of memristive neural networks with time delays, 2014.
Sun, 2020, Quantized synchronization of memristive neural networks with time-varying delays via super-twisting algorithm, Neurocomputing, 380, 133, 10.1016/j.neucom.2019.11.003
Sun, 2020, Synchronization of discrete-time recurrent neural networks with time-varying delays via quantized sliding mode control, Appl. Math. Comput., 1
Xu, 2018, Periodic dynamics for memristor-based bidirectional associative memory neural networks with leakage delays and time-varying delays, Int. J. Control Autom. Syst., 16, 535, 10.1007/s12555-017-0235-7
S. Mitsui, K.M. Igarashi, K. Mori, Y. Yoshihara, Control System Synthesis: A Factorization Approach, Part II, 1985.
Gao, 2011, Sampled-data based consensus of continuous-time multi-agent systems with time-varying topology, IEEE Trans. Autom. Control, 56, 1226, 10.1109/TAC.2011.2112472
Nghiem, 2012, Time-triggered implementations of dynamic controllers, ACM Trans. Embedded Comput. Syst., 11, 1, 10.1145/2331147.2331168
Tabuada, 2007, Event-triggered real-time scheduling of stabilizing control tasks, IEEE Trans. Autom. Control, 52, 1680, 10.1109/TAC.2007.904277
Yue, 2013, A delay system method for designing event-triggered controllers of networked control systems, IEEE Trans. Autom. Control, 58, 475, 10.1109/TAC.2012.2206694
Li, 2015, Event-triggering sampling based leader-following consensus in second-order multi-agent systems, IEEE Trans. Autom. Control, 60, 1998, 10.1109/TAC.2014.2365073
Wu, 2017, Event-triggered sliding mode control of stochastic systems via output feedback, Automatica, 82, 79, 10.1016/j.automatica.2017.04.032
L.B. Groff, L.G. Moreira, J.M. Gomes da Silva, D. Sbarbaro, Observer-based event-triggered control: A discrete-time approach, in: 2016 American Control Conference (ACC), 2016, pp. 4245–4250.
Fei, 2018, Exponential synchronization of networked chaotic delayed neural network by a hybrid event trigger scheme, IEEE Trans. Neural Netw. Learn. Syst., 29, 2558, 10.1109/TNNLS.2017.2700321
Wang, 2020, Projective synchroniztion of neural networks via continuous/periodic event-based sampling algorithms, IEEE Trans. Network Sci. Eng., 1
Z. Guo, S. Gong, S. Wen, T. Huang, Event-based synchronization control for memristive neural networks with time-varying delay, IEEE Trans. Cybern. 99 (2019) 3268–3277.
Cao, 2020, Exponential synchronization of switched neural networks with mixed time-varying delays via static/dynamic event-triggering rules, IEEE Access, 8, 338, 10.1109/ACCESS.2019.2955939
Brogliato, 2013, Dissipative systems analysis and control, Theory Appl., 12, 2211
Wang, 2017, Passivity analysis of coupled reaction-diffusion neural networks with dirichlet boundary conditions, IEEE Trans. Syst. Man Cybern., 47, 2148, 10.1109/TSMC.2016.2622363
Chua, 1999, Passivity and complexity, IEEE Trans. Circuits Syst. I, 46, 71, 10.1109/81.739186
Mahmoud, 2006, Passivity and passification of time-delay systems, J. Math. Anal. Appl., 292, 247, 10.1016/j.jmaa.2003.11.055
Guo, 2014, Passivity and passification of memristor-based recurrent neural networks with time-varying delays, IEEE Trans. Neural Netw. Learn. Syst., 25, 2099, 10.1109/TNNLS.2014.2305440
Yao, 2009, Passive stability and synchronization of complex spatio-temporal switching networks with time delays, Automatica, 45, 1721, 10.1016/j.automatica.2009.02.030
Wang, 2019, Sliding mode control of neural networks via continuous or periodic sampling event-triggering algorithm, Neural Networks, 121, 140, 10.1016/j.neunet.2019.09.001
Wen, 2016, Aperiodic sampled-data sliding-mode control of fuzzy systems with communication delays via the event-triggered method, IEEE Trans. Fuzzy Syst., 24, 1048, 10.1109/TFUZZ.2015.2501412
Guo, 2019, Multistability of switched neural networks with piecewise linear activation functions under state-dependent switching, IEEE Trans. Neural Netw. Learn. Syst., 30, 2052, 10.1109/TNNLS.2018.2876711
Li, 2009, Robust stability for uncertain delayed fuzzy Hopfield neural networks with Markovian jumping parameters, IEEE Trans. Syst. Man Cybern. Part B (Cybernetics), 39, 94, 10.1109/TSMCB.2008.2002812
Cao, 2019, Passivity analysis of reaction-diffusion memristor-based neural networks with and without time-varying delays, Neural Networks, 109, 159, 10.1016/j.neunet.2018.10.004
Khalil, 2002
Wen, 2017, Sliding-mode control of memristive Chua’s systems via the event-based method, IEEE Trans. Circuits Syst. II Express Briefs, 64, 81
Behera, 2018, Periodic event-triggered sliding mode control, Automatica, 96, 61, 10.1016/j.automatica.2018.06.035
Li, 2019, Mittag-Leffler stability for a new coupled system of fractional-order differential equations with impulses, Appl. Math. Comput., 361, 22, 10.1016/j.amc.2019.05.018
H. Li, Y. Kao, Synchronous stability of the fractional-order discrete-time dynamical network system model with impulsive couplings, Neurocomputing.
Meng, 2020, Global Mittag-Leffler stability for fractional-order coupled systems on network without strong connectedness, Sci. China-Inf. Sci., 63, 10.1007/s11432-019-9946-6
Rakkiyappan, 2015, Passivity and passification of memristor-based recurrent neural networks with additive time-varying delays, IEEE Trans. Neural Netw. Learn. Syst., 26, 2043, 10.1109/TNNLS.2014.2365059
Cheng, 2020, Nonstationary l2-l∞ filtering for Markov switching repeated scalar nonlinear systems with randomly occurring nonlinearities, Appl. Math. Comput., 365, 10.1016/j.amc.2019.124714
Cheng, 2019, Quantized nonstationary filtering of network-based Markov switching RSNSs: a multiple hierarchical structure strategy, IEEE Trans. Autom. Control, 99, 1
Cheng, 2020, A hidden mode observation approach to finite-time SOFC of Markovian switching systems with quantization, Nonlinear Dyn., 99, 1