Abstract
This paper investigates the stability and stabilization of inertial memristive neural networks (IMNNs) with discrete and unbounded distributed delays. The considered IMNNs are described as hybrid neural systems with second-order derivatives due to the combination of memristor and inertial items. By invoking an appropriate variable substitution method, the hybrid neural system is turned into a first-order differential system. Then, based on the nonsmooth analysis and Lyapunov stability theories, several new algebraic conditions for the global stability of IMNNs with unbounded distributed delays are derived. In addition, two simple classes of feedback control laws are designed for the considered IMNNs and the corresponding stabilizability criteria are established. Finally, two numerical examples and their discussions are provided to illustrate the validity and superiority of the theoretical results.
Similar content being viewed by others
References
Strukov, D.B., Snider, G.S., Stewart, G.R., Williams, R.S.: The missing memristor found. Nature 453, 80–83 (2008)
Jo, S.H., Chang, T., Ebong, I., Bhadviya, B.B., Mazumder, P., Lu, W.: Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett. 10(4), 1297–1301 (2010)
Chua, L.O.: Memristor-the missing circuit element. IEEE Trans. Circuit Theory 18, 507–519 (1971)
Sharifi, M.J., Banadaki, Y.M.: General SPICE models for memristor and application to circuit simulation of memristor-based synapses and memory cells. J. Circuits Syst. Comput. 19, 407–424 (2010)
Hu, J., Wang, J.: Global uniform asymptotic stability of memristor-based recurrent neural networks with time delays. In International Joint Conference on Neural Network IJCNN, pp. 1–8 (2010)
Bao, H., Park, J.H., Cao, J.: Adaptive synchronization of fractional-order memristor-based neural networks with time delay. Nonlinear Dyn. 82(3), 1343–1354 (2015)
Wu, A., Zeng, Z.: Exponential stabilization of memristive neural networks with time delays. IEEE Trans. Neural Netw. Learn. Syst. 23, 1919–1929 (2012)
Wang, Z., Ding, S., Huang, Z., Zhang, H.: Exponential stability and stabilization of delayed memristive neural networks based on quadratic convex combination method. IEEE Trans. Neural Netw. Learn. Syst. 27, 2337–2350 (2016)
Zhang, R., Zeng, D., Zhong, S., Yu, Y.: Event-triggered sampling control for stability and stabilization of memristive neural networks with communication delays. Appl. Math. Comput. 310, 57–74 (2017)
Zheng, M., et al.: Finite-time projective synchronization of memristor-based delay fractional-order neural networks. Nonlinear Dyn. 89(4), 2641–2655 (2017)
Guo, Z., Wang, J., Yan, Z.: Global exponential dissipativity and stabilization of memristor-based recurrent neural networks with time-varying delays. Neural Netw. 48, 158–172 (2013)
Wen, S., Huang, T., Zeng, Z., Chen, Y., Li, P.: Circuit design and exponential stabilization of memristive neural networks. Neural Netw. 63, 48–56 (2015)
Abdurahman, A., Jiang, H., Teng, Z.: Exponential lag synchronization for memristor-based neural networks with mixed time delays via hybrid switching control. J. Frankl. Inst. 353(13), 2859–2880 (2016)
Duan, S., Hu, X., Dong, Z., Wang, L., Mazumder, P.: Memristor-based cellular nonlinear/neural network: design, analysis, and applications. IEEE Trans. Neural Netw. Learn. Syst. 26(6), 1202–1213 (2015)
Zhang, H., Wang, Z., Liu, D.: A comprehensive review of stability analysis of continuous-time recurrent neural networks. IEEE Trans. Neural Netw. Learn. Syst. 25, 1229–1262 (2014)
Wu, A., Zeng, Z.: Lagrange stability of memristive neural networks with discrete and distributed delays. IEEE Trans. Neural Netw. Learn. Syst. 25(4), 690–703 (2014)
Wang, X., Li, C., Huang, T., Chen, L.: Dual-stage impulsive control for synchronization of memristive chaotic neural networks with discrete and continuously distributed delays. Neurocomputing 149, 621–628 (2015)
Zhang, G., Shen, Y., Yin, Q., Sun, J.: Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays. Neural Netw. 61, 49–58 (2015)
Jiang, P., Zeng, Z., Chen, J.: Almost periodic solutions for a memristor-based neural networks with leakage, time-varying and distributed delays. Neural Netw. 68, 34–45 (2015)
Wang, L., Zeng, Z., Ge, M.-F., Hu, J.: Global stabilization analysis of inertial memristive recurrent neural networks with discrete and distributed delays. Neural Netw. 105, 65–74 (2018)
Song, Q., Zhao, Z., Liu, Y.: Impulsive effects on stability of discrete-time complex-valued neural networks with both discrete and distributed time-varying delays. Neurocomputing 168, 1044–1050 (2015)
Song, Q., Yu, Q., Zhao, Z., Liu, Y., Alsaadi, F.E.: Dynamics of complex-valued neural networks with variable coefficients and proportional delays. Neurocomputing 275, 2762–2768 (2018)
Song, Q., Yu, Q., Zhao, Z., Liu, Y., Alsaadi, F.E.: Boundedness and global robust stability analysis of delayed complex-valued neural networks with interval parameter uncertainties. Neural Netw. 103, 55–62 (2018)
Angelaki, D.E., Correia, M.J.: Models of membrane resonance in pigeon semicircular canal type II hair cells. Biol. Cybern. 65(1), 1–10 (1991)
Wheeler, D.W., Schieve, W.C.: Stability and chaos in an inertial two-neuron system. Physica D 105, 267–284 (1997)
Liu, Q., Liao, X., Liu, Y., Zhou, S., Guo, S.: Dynamics of an inertial two-neuron system with time delay. Nonlinear Dyn. 58(3), 573 (2009)
Cao, J., Wan, Y.: Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays. Neural Netw. 53, 165–172 (2014)
Lakshmanan, S., et al.: Synchronization of an inertial neural network with time-varying delays and its application to secure communication. IEEE Trans. Neural Netw. Learn. Syst. 29, 195–207 (2018)
Tu, Z., Cao, J., Hayat, T.: Global exponential stability in Lagrange sense for inertial neural networks with time-varying delays. Neurocomputing 171, 524–531 (2016)
Zhang, W., Li, C., Huang, T., Tan, J.: Exponential stability of inertial BAM neural networks with time-varying delay via periodically intermittent control. Neural Comput. Appl. 26, 1781–1787 (2015)
Li, X., Li, X., Hu, C.: Some new results on stability and synchronization for delayed inertial neural networks based on non-reduced order method. Neural Netw. 96, 91–100 (2017)
Kwon, O.M., Park, J.H., Lee, S.M., Cha, E.J.: New augmented Lyapunov–Krasovskii functional approach to stability analysis of neural networks with time-varying delays. Nonlinear Dyn. 76(1), 221–236 (2014)
Wang, L., Zeng, Z., Hu, J., Wang, X.: Controller design for global fixed-time synchronization of delayed neural networks with discontinuous activations. Neural Netw. 87, 122–131 (2017)
Rakkiyappan, R., Premalatha, S., Chandrasekar, A., Cao, J.: Stability and synchronization analysis of inertial memristive neural networks with time delays. Cognit. Neurodyn. 10, 437–451 (2016)
Zhang, G., Zeng, Z.: Exponential stability for a class of memristive neural networks with mixed time-varying delays. Appl. Math. Comput. 321, 544–554 (2018)
Zhang, W., Huang, T., He, X., Li, C.: Global exponential stability of inertial memristor-based neural networks with time-varying delays and impulses. Neural Netw. 95, 102–109 (2017)
Tu, Z., Cao, J., Alsaedi, A., Alsaadi, F.: Global dissipativity of memristor-based neutral type inertial neural networks. Neural Netw. 88, 125–133 (2017)
Zhang, G., Zeng, Z., Hu, J.: New results on global exponential dissipativity analysis of memristive inertial neural networks with distributed time-varying delays. Neural Netw. 97, 183–191 (2018)
Xiao, Q., Huang, Z., Zeng, Z.: Passivity analysis for memristor-based inertial neural networks with discrete and distributed dlays. IEEE Trans. Syst. Man Cybern. Syst. https://doi.org/10.1109/TSMC.2017.2732503
Huang, D., Jiang, M., Jian, J.: Finite-time synchronization of inertial memristive neural networks with time-varying delays via sampled-date control. Neurocomputing 266, 527–539 (2017)
Wei, R., Cao, J., Alsaedi, A.: Finite-time and fixed-time synchronization analysis of inertial memristive neural networks with time-varying delays. Cognit. Neurodyn. 12, 121–134 (2018)
Gong, S., Yang, S., Guo, Z., Huang, T.: Global exponential synchronization of inertial memristive neural networks with time-varying delay via nonlinear controller. Neural Netw. 102, 138–148 (2018)
Wang, L., Ge, M.-F., Zeng, Z., Hu, J.: Finite-time robust consensus of nonlinear disturbed multiagent systems via two-layer event-triggered control. Inf. Sci. 466, 270–283 (2018)
Zhang, R., Liu, X., Zeng, D., Zhong, S., Shi, K.: A novel approach to stability and stabilization of fuzzy sampled-data Markovian chaotic systems. Fuzzy Sets Syst. https://doi.org/10.1016/j.fss.2017.12.010
Zhang, R., Zeng, D., Park, J.H., Liu, Y., Zhong, S.: A new approach to stabilization of chaotic systems with nonfragile fuzzy proportional retarded sampled-data control. IEEE Trans. Cybern. https://doi.org/10.1109/TCYB.2018.2831782
Filippov, A.F.: Differential Equations with Discontinuous Right-hand Sides. Kluwer, Dordrecht (1988)
Clarke, F.H., Ledyaev, Y.S., Stem, R.J., Wolenski, R.R.: Nonsmooth Analysis and Control Theory. Springer, New York (1998)
Acknowledgements
This work was supported by the National Natural Science Foundation of China under Grants 61703377, 61703374, 61876192, and 61603419, and the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) under Grants CUG170632 and CUG170656.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Rights and permissions
About this article
Cite this article
Wang, L., Ge, MF., Hu, J. et al. Global stability and stabilization for inertial memristive neural networks with unbounded distributed delays. Nonlinear Dyn 95, 943–955 (2019). https://doi.org/10.1007/s11071-018-4606-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11071-018-4606-2