Finite-time synchronisation and passivity of coupled memristive neural networks

References

• Aghababa, M. P., & Aghababa, H. P. (2012). A general nonlinear adaptive control scheme for finite-time synchronization of chaotic systems with uncertain parameters and nonlinear inputs. Nonlinear Dynamics, 69(4), 1903–1914. doi: 10.1007/s11071-012-0395-1
   Web of Science ®Google Scholar
• Chen, W. Z., Huang, Y. L., & Ren, S. Y. (2018). Passivity of coupled memristive delayed neural networks with fixed and adaptive coupling weights. Neurocomputing. doi:10.1016/j.neucom.2018.06.019
   Google Scholar
• Chen, C., Li, L., Peng, H., Yang, Y., & Li, T. (2017). Finite-time synchronization of memristor-based neural networks with mixed delays. Neurocomputing, 235, 83–89. doi: 10.1016/j.neucom.2016.12.061
   Web of Science ®Google Scholar
• Chua, L. O. (1971). Memristor-the missing circuit element. IEEE Transactions on Circuit Theory, 18, 507–519. doi: 10.1109/TCT.1971.1083337
   Google Scholar
• Du, Y., & Xu, R. (2014). Robust synchronization of an array of neural networks with hybrid coupling and mixed time delays. ISA Transactions, 53, 1015–1023. doi: 10.1016/j.isatra.2014.03.005
   PubMed Web of Science ®Google Scholar
• Efimov, D., Polyakov, A., Fridman, E., Perruquetti, W., & Richard, J. (2014). Comments on finite-time stability of time-delay systems. Automatica, 50, 1944–1947. doi: 10.1016/j.automatica.2014.05.010
   Web of Science ®Google Scholar
• Fu, Q., Cai, J., Zhong, S., & Yu, Y. (2018). Dissipativity and passivity analysis for memristor-based neural networks with leakage and two additive time-varying delays. Neurocomputing, 275, 747–757. doi: 10.1016/j.neucom.2017.09.014
   Web of Science ®Google Scholar
• Huang, Y. L., & Wang, S. X. (2018). Synchronisation in an array of spatial diffusion coupled reaction-diffusion neural networks via pinning control. International Journal of Systems Science, 49, 1103–1118. doi: 10.1080/00207721.2018.1431700
   Web of Science ®Google Scholar
• Huang, Y. L., Wang, S. X., & Ren, S. Y. (2017). Pinning exponential synchronisation and passivity of coupled delayed reaction-diffusion neural networks with and without parametric uncertainties. International Journal of Control. doi:10.1080/00207179.2017.1384575
   Google Scholar
• Huang, Y. L., Xu, B. B., & Ren, S. Y. (2018). Analysis and pinning control for passivity of coupled reaction-diffusion neural networks with nonlinear coupling. Neurocomputing, 272, 334–342. doi: 10.1016/j.neucom.2017.07.010
   Web of Science ®Google Scholar
• Huang, B., Zhang, H., Gong, D., & Wang, J. (2015). Synchronization analysis for static neural networks with hybrid couplings and time delays. Neurocomputing, 148, 288–293. doi: 10.1016/j.neucom.2013.11.053
   Web of Science ®Google Scholar
• Itoh, M., & Chua, L. O. (2009). Memristor cellular automata and memristor discrete-time cellular neural networks. International Journal of Bifurcation and Chaos, 19(11), 3605–3656. doi: 10.1142/S0218127409025031
   Web of Science ®Google Scholar
• Li, D., & Cao, J. (2015). Finite-time synchronization of coupled networks with one single time-varying delay coupling. Neurocomputing, 166, 265–270. doi: 10.1016/j.neucom.2015.04.013
   Web of Science ®Google Scholar
• Li, N., & Cao, J. (2016a). Lag synchronization of memristor-based coupled neural networks via ω-measure. IEEE Transactions on Neural Networks and Learning Systems, 27, 686–697. doi: 10.1109/TNNLS.2015.2480784
   PubMed Web of Science ®Google Scholar
• Li, N., & Cao, J. (2016b). Passivity and robust synchronisation of switched interval coupled neural networks with time delay. International Journal of Systems Science, 47, 2827–2836. doi: 10.1080/00207721.2015.1029570
   Web of Science ®Google Scholar
• Li, N., Cao, J., Alsaedi, A., & Alsaadi, F. (2017). Lag synchronization criteria for memristor-based coupled neural networks via parameter mismatches analysis approach. Neural Computation, 29, 1721–1744. doi: 10.1162/NECO_a_00918
   PubMed Web of Science ®Google Scholar
• Liu, X., & Wei, Y. (2016). Finite-time cluster synchronization of nonlinearly coupled reaction-diffusion neural networks via spatial coupling and control. In Proceedings of the 3rd International Conference on Systems and Informatics, 24–29.
   Google Scholar
• Liu, Y., & Zhao, J. (2012). Generalized output synchronization of dynamical networks using output quasi-passivity. IEEE Transactions on Circuits and Systems-I: Regular Papers, 59, 1290–1298. doi: 10.1109/TCSI.2011.2173391
   Web of Science ®Google Scholar
• Liu, D., Zhu, S., & Ye, E. (2017). Synchronization stability of memristor-based complex-valued neural networks with time delays. Neural Networks, 96, 115–127. doi: 10.1016/j.neunet.2017.09.008
   PubMed Web of Science ®Google Scholar
• Ma, C. Q., Li, T., & Zhang, J. F. (2010). Consensus control for leader-following multi-agent systems with measurement noises. Journal of Systems Science and Complexity, 23, 35–49. doi: 10.1007/s11424-010-9273-4
   Web of Science ®Google Scholar
• Ma, C. Q., & Zhang, J. F. (2010). On formability of linear continuous-time multi-agent systems. Journal of Systems Science and Complexity, 25, 13–29. doi: 10.1007/s11424-012-0108-3
   Web of Science ®Google Scholar
• Meng, Z., & Xiang, Z. (2015). Passivity analysis of memristor-based recurrent neural networks with mixed time-varying delays. Neurocomputing, 165, 270–279. doi: 10.1016/j.neucom.2015.03.016
   Web of Science ®Google Scholar
• Pershin, Y. V., & Di Ventra, M. (2010). Experimental demonstration of associative memory with memristive neural networks. Neural Network, 23, 881–886. doi: 10.1016/j.neunet.2010.05.001
   PubMed Web of Science ®Google Scholar
• Qian, C., & Li, J. (2005). Global finite-time stabilization by output feedback for planar systems without observable linearization. IEEE Transactions on Automatic Control, 50, 885–890. doi: 10.1109/TAC.2005.849253
   Web of Science ®Google Scholar
• Shen, J., & Cao, J. (2011). Finite-time synchronization of coupled neural networks via discontinuous controllers. Cognitive Neurodynamics, 5, 373–385. doi: 10.1007/s11571-011-9163-z
   PubMed Web of Science ®Google Scholar
• Shi, L., Yang, X., Li, Y., & Feng, Z. (2016). Finite-time synchronization of nonidentical chaotic systems with multiple time-varying delays and bounded perturbations. Nonlinear Dynamics, 83(1-2), 75–87. doi: 10.1007/s11071-015-2310-z
   Web of Science ®Google Scholar
• Su, L., & Zhou, L. (2017). Passivity of memristor-based recurrent neural networks with multi-proportional delays. Neurocomputing, 266, 485–493. doi: 10.1016/j.neucom.2017.05.064
   Web of Science ®Google Scholar
• Tang, Y. (1998). Terminal sliding mode control for rigid robots. Automatica, 34, 51–56. doi: 10.1016/S0005-1098(97)00174-X
   Web of Science ®Google Scholar
• Thomas, A. (2013). Memristor-based neural networks. Journal of Physics D Applied Physics, 46(9), 093001. doi: 10.1088/0022-3727/46/9/093001
   Web of Science ®Google Scholar
• Wan, Y., & Cao, J. (2015). Periodicity and synchronization of coupled memristive neural networks with supremums. Neurocomputing, 159, 137–143. doi: 10.1016/j.neucom.2015.02.007
   Web of Science ®Google Scholar
• Wan, P., & Jian, J. (2018). Passivity analysis of memristor-based impulsive inertial neural networks with time-varying delays. ISA Transactions, 74, 88–98. doi: 10.1016/j.isatra.2018.02.002
   PubMed Web of Science ®Google Scholar
• Wang, W. P., Li, L. X., Peng, H. P., Wang, W. N., Kurths, J., Xiao, J. H., & Yang, Y. X (2016). Anti-synchronization of coupled memristive neutral-type neural networks with mixed time-varying delays via randomly occurring control. Nonlinear Dynamics, 83, 2143–2155. doi: 10.1007/s11071-015-2471-9
   Web of Science ®Google Scholar
• Wang, X., She, K., Zhong, S., & Cheng, J. (2017). Exponential synchronization of memristor-based neural networks with time-varying delay and stochastic perturbation. Neurocomputing, 242, 131–139. doi: 10.1016/j.neucom.2017.02.059
   Web of Science ®Google Scholar
• Wang, J. L., Wu, H. N., & Huang, T. W. (2015). Passivity-based synchronization of a class of complex dynamical networks with time-varying delay. Automatica, 56, 105–112. doi: 10.1016/j.automatica.2015.03.027
   Web of Science ®Google Scholar
• Wang, J. L., Wu, H. N., Huang, T., & Ren, S. Y. (2015). Passivity and synchronization of linearly coupled reaction-diffusion neural networks with adaptive coupling. IEEE Transactions on Cybernetics, 45, 1942–1952. doi: 10.1109/TCYB.2014.2362655
   PubMed Web of Science ®Google Scholar
• Wang, J. L., Wu, H. N., Huang, T. W., & Ren, S. Y. (2016). Pinning control strategies for synchronization of linearly coupled neural networks with reaction-diffusion terms. IEEE Transactions on Neural Networks and Learning Systems, 27, 749–761. doi: 10.1109/TNNLS.2015.2423853
   PubMed Web of Science ®Google Scholar
• Wang, J. L., Wu, H. N., Huang, T., Ren, S. Y., & Wu, J. G. (2017a). Passivity analysis of coupled reaction-diffusion neural networks with Dirichlet boundary conditions. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47, 2148–2159. doi: 10.1109/TSMC.2016.2622363
   Web of Science ®Google Scholar
• Wang, J. L., Wu, H. N., Huang, T. W., Ren, S. Y., & Wu, J. G. (2017b). Passivity of directed and undirected complex dynamical networks with adaptive coupling weights. IEEE Transactions on Neural Networks and Learning Systems, 28, 1827–1839. doi: 10.1109/TNNLS.2016.2558502
   PubMed Web of Science ®Google Scholar
• Wang, J. L., Wu, H. N., Huang, T. W., & Xu, M. (2017). Output synchronization in coupled neural networks with and without external disturbances. IEEE Transactions on Control of Network Systems. doi:10.1109/TCNS.2017.2782488
   Google Scholar
• Wang, J. L., Xu, M., Wu, H. N., & Huang, T. W. (2017). Finite-time passivity of coupled neural networks with multiple weights. IEEE Transactions on Network Science and Engineering. doi:10.1109/TNSE.2017.2746759
   PubMed Web of Science ®Google Scholar
• Wu, Y., Cao, J., Li, Q., Alsaedi, A., & Alsaadi, F. E. (2017). Finite-time synchronization of uncertain coupled switched neural networks under asynchronous switching. Neural Networks, 85, 128–139. doi: 10.1016/j.neunet.2016.10.007
   PubMed Web of Science ®Google Scholar
• Xu, B. B., Huang, Y. L., Wang, J. L., Wei, P. C., & Ren, S. Y. (2016). Passivity of linearly coupled neural networks with reaction-diffusion terms and switching topology. Journal of the Franklin Institute, 353, 1882–1898. doi: 10.1016/j.jfranklin.2016.03.004
   Web of Science ®Google Scholar
• Yang, X. (2014). Can neural networks with arbitrary delays be finite-timely synchronized?. Neurocomputing, 143, 275–281. doi: 10.1016/j.neucom.2014.05.064
   Web of Science ®Google Scholar
• Yang, X., Cao, J., & Yu, W. (2014). Exponential synchronization of memristive Cohen-Grossberg neural networks with mixed delays. Cognitive Neurodynamics, 8, 239–249. doi: 10.1007/s11571-013-9277-6
   PubMed Web of Science ®Google Scholar
• Yang, S. F., Guo, Z. Y., & Wang, J. (2015). Robust synchronization of multiple memristive neural networks with uncertain parameters via nonlinear coupling. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45, 1077–1086. doi: 10.1109/TSMC.2014.2388199
   Web of Science ®Google Scholar
• Yang, X., & Ho, D. (2016). Synchronization of delayed memristive neural networks: Robust analysis approach. IEEE Transactions on Cybernetics, 46, 3377–3387. doi: 10.1109/TCYB.2015.2505903
   PubMed Web of Science ®Google Scholar
• Yang, X., Ho, D., Lu, J., & Song, Q. (2015). Finite-time cluster synchronization of T-S fuzzy complex networks with discontinuous subsystems and random coupling delays. IEEE Transactions on Fuzzy Systems, 23(6), 2302–2316. doi: 10.1109/TFUZZ.2015.2417973
   Web of Science ®Google Scholar
• Yang, Z., Luo, B., Liu, D., & Li, Y. (2017). Pinning synchronization of memristor-based neural networks with time-varying delays. Neural Networks, 93, 143–151. doi: 10.1016/j.neunet.2017.05.003
   PubMed Web of Science ®Google Scholar
• Yang, X., Song, Q., Liang, J., & He, B. (2015). Finite-time synchronization of coupled discontinuous neural networks with mixed delays and nonidentical perturbations. Journal of the Franklin Institute, 352, 4382–4406. doi: 10.1016/j.jfranklin.2015.07.001
   Web of Science ®Google Scholar
• Yu, H., & Antsaklis, P. J. (2014). Output synchronization of networked passive systems with event-driven communication. IEEE Transactions on Automatic Control, 59, 750–756. doi: 10.1109/TAC.2013.2274704
   Web of Science ®Google Scholar
• Zhang, B., Deng, F., Xie, S., & Luo, S. (2018). Exponential synchronization of stochastic time-delayed memristor-based neural networks via distributed impulsive control. Neurocomputing, 286, 41–50. doi: 10.1016/j.neucom.2018.01.051
   Web of Science ®Google Scholar
• Zhang, G., Shen, Y., Yin, Q., & Sun, J. (2015). Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays. Neural Networks, 61, 49–58. doi: 10.1016/j.neunet.2014.10.004
   PubMed Web of Science ®Google Scholar
• Zheng, Z., Huang, Y., Xie, L., & Zhu, B. (2017). Adaptive trajectory tracking control of a fully actuated surface vessel with asymmetrically constrained input and output. IEEE Transactions on Control Systems Technology. doi:10.1109/TCST.2017.2728518
   Google Scholar
• Zheng, Z., Sun, L., & Xie, L. (2017). Error constrained LOS path following of a surface vessel with actuator saturation and faults. IEEE Transactions on Systems, Man and Cybernetics: Systems. doi:10.1109/TSMC.2017.2717850
   Web of Science ®Google Scholar
• Zhou, L. L., Wang, C. H., He, H. Z., & Lin, Y. (2015). Time-controllable combinatorial inner synchronization and outer synchronization of anti-star networks and its application in secure communication. Communications in Nonlinear Science and Numerical Simulation, 22(1–3), 623–640. doi: 10.1016/j.cnsns.2014.07.006
   Web of Science ®Google Scholar