logo

Journals Books
Advanced Search
Sign in Register

中文

SCIENCE CHINA Information Sciences
Download PDF
SCIENCE CHINA Information Sciences, Volume 60 , Issue 3 : 032201(2017) https://doi.org/10.1007/s11432-016-0555-2

Fixed-time synchronization of delayed memristor-based recurrent neural networks

Jinde CAO , Ruoxia LI
More info
  • ReceivedAug 17, 2016
  • AcceptedSep 29, 2016
  • PublishedJan 23, 2017
Previous Table of Contents Next
Share
Rating

Abstract


Acknowledgment

Acknowledgments

This work was jointly supported by National Natural Science Foundation of China (Grant Nos. 61573096, 61272530), Natural Science Foundation of Jiangsu Province of China (Grant No. BK2012741), and ``333 Engineering'' Foundation of Jiangsu Province of China (Grant No. BRA2015286), and Scientific Research Foundation of Graduate School of Southeast University (Grant No. YBJJ1663).


References

[1] Chua L O. Memristor-the missing circut element. IEEE Trans Circ Theory, 1971, 18: 507-519 CrossRef Google Scholar

[2] Chua L O, Kang S M. Memristive devices and systems. Proc IEEE, 1976, 64: 209-223 CrossRef Google Scholar

[3] Strukov D B, Snider G S, Stewart D R, et al. The missing memristor found. Nature, 2008, 453: 80-83 CrossRef Google Scholar

[4] Snider G S. Self-organized computation with unreliable, memristive nanodevices. Nanotechnology, 2007, 18: 365202-83 CrossRef Google Scholar

[5] Wen S P, Zeng Z G, Huang T W, et al. Fuzzy modeling and synchronization of different memristor-based chaotic circuits. Phys Lett A, 2013, 377: 2016-2021 CrossRef Google Scholar

[6] Landsman A S, Schwartz I B. Complete chaotic synchronization in mutually coupled time-delay systems. Phys Rev E Stat Nonlin Soft Matter Phys, 2007, 5: 26-33 Google Scholar

[7] Cui B T, Lou X Y. Synchronization of chaotic recurrent neural networks with time-varying delays using nonlinear feedback control. Chaos Solitons Fract, 2009, 39: 288-294 CrossRef Google Scholar

[8] Gan Q T, Xu R, Kang X B. Synchronization of chaotic neural networks with mixed time delays. Commun Nonlinear Sci Numer Simul, 2011, 16: 966-974 CrossRef Google Scholar

[9] Molaei M R, Umut Ö. Generalized synchronization of nuclear spin generator system. Chaos Solitons Fract, 2008, 37: 227-232 CrossRef Google Scholar

[10] Cao J D, Rakkiyappan R, Maheswari K, et al. Exponential $H_\infty$ filtering analysis for discrete-time switched neural networks with random delays using sojourn probabilities. Sci China Tech Sci, 2016, 59: 387-402 CrossRef Google Scholar

[11] Suddheerm K S, Sabir M. Adaptive function projective synchronization of two-cell Quantum-CNN chaotic oscillators with uncertain parameters. Phys Lett A, 2009, 373: 1847-1851 CrossRef Google Scholar

[12] Chen S, Cao J D. Projective synchronization of neural networks with mixed time-varying delays and parameter mismatch. Nonlinear Dyn, 2012, 67: 1397-1406 CrossRef Google Scholar

[13] Cao J D, Li L L. Cluster synchronization in an array of hybrid coupled neural networks with delay. Neural Netw, 2009, 22: 335-342 CrossRef Google Scholar

[14] Li X D, Bohner M. Exponential synchronization of chaotic neural networks with mixe ddelays and impulsive effects via output coupling with delay feedback. Math Comp Model, 2010, 52: 643-653 CrossRef Google Scholar

[15] Cao J D, Sivasamy R, Rakkaiyappan R. Sampled-data $H_{\infty}$ synchronization of chaotic Lur'e systems with time delay. Circ Syst Sign Process, 2016, 35: 811-835 CrossRef Google Scholar

[16] Yang S F, Guo Z Y, Wang J. Global synchronization of multiple recurrent neural networks with time delays via impulsive interactions. IEEE Trans Neural Netw Learn Syst, in press. doi: 10.1109/TNNLS.2016.2549703. Google Scholar

[17] Ding S B, Wang Z S. Stochastic exponential synchronization control of memristive neural networks with multiple time-varying delays. Neurocomputing, 2015, 162: 16-25 CrossRef Google Scholar

[18] Li R X, Wei H Z. Synchronization of delayed Markovian jump memristive neural networks with reaction-diffusion terms via sampled data control. Int J Mach Learn Cyber, 2016, 7: 157-169 CrossRef Google Scholar

[19] Abdurahman A, Jiang H J, Teng Z D. Finite-time synchronization for memristor-based neural networks with time-varying delays. Neural Netw, 2015, 69: 20-28 CrossRef Google Scholar

[20] Wang L M, Shen Y, Yin Q, et al. Adaptive synchronization of memristor-based neural networks with time-varying delays. IEEE Trans Neural Netw Learn Syst, 2015, 26: 2033-2042 CrossRef Google Scholar

[21] Chen J J, Zeng Z G, Jiang P. Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks. Neural Netw, 2014, 51: 1-8 CrossRef Google Scholar

[22] Wen S P, Zeng Z G, Huang T W, et al. Exponential adaptive lag synchronization of memristive neural networks via fuzzy method and applications in pseudorandom number generators. IEEE Trans Fuzzy Syst, 2014, 22: 1704-1713 CrossRef Google Scholar

[23] Ding S B, Wang Z S. Lag quasi-synchronization for memristive neural networks with switching jumps mismatch. Neural Comput Appl, in press. doi: 10.1007/s00521-016-2291-y. Google Scholar

[24] Yang S F, Guo Z Y, Wang J. Robust synchronization of multiple memristive neural networks with uncertain parameters via nonlinear coupling. IEEE Trans Syst Man Cyber Syst, 2015, 45: 1077-1086 CrossRef Google Scholar

[25] Wan Y, Cao J D. Periodicity and synchronization of coupled memristive neural networks with supremums. Neurocomputing, 2015, 159: 137-143 CrossRef Google Scholar

[26] Polyakov A. Nonlinear feedback design for fixed-time stabilization of linear control systems. IEEE Trans Autom Control, 2012, 57: 2106-2110 CrossRef Google Scholar

[27] Levant A. On fixed and finite time stability in sliding mode control. In: Proceedings of the 52nd IEEE Conference on Decision and Control, Florence, 2013. 4260--4265. Google Scholar

[28] Parsegv S, Polyakov A, Shcherbakov P. Nonlinear fixed-time control protocol for uniform allocation of agents on a segment. In: Proceedings of the 51st IEEE Conference on Decision and Control, Maui, 2013. 7732--7737. Google Scholar

[29] Parsegv S, Polyakov A, Shcherbakov P. On fixed and finite time stability in sliding mode control. In: Proceedings of the 4th IFAC Workshop on Distributed Estimation and Control in Networked Systems, Koblenz, 2013. 110--115. Google Scholar

[30] Zhou Y J, Sun C Y. Fixed time synchronization of complex dynamical networks. In: Proceedings of the Chinese Intelligent Automation Conference. Berlin: Springer, 2015. 338: 163--170. Google Scholar

[31] Zuo Z. Non-singular fixed-time terminal sliding mode control of non-linear systems. IET Control Theory Appl, 2015, 9: 545-552 CrossRef Google Scholar

[32] Liu X W, Chen T P. Fixed-time cluster synchronization for complex networks via pinning control. arXiv:1509.03350. Google Scholar

[33] Wan Y, Cao J D, Wen G H, et al. Robust fixed-time synchronization of delayed Cohen-Grossberg neural networks. Neural Netw, 2016, 73: 86-94 CrossRef Google Scholar

[34] Clarke F. Optimization and Nonsmooth Analysis. Philadelphia: SIAM, 1987. Google Scholar

[35] Hardy G, Littlewood J, Polya G. Inequalities. 2nd ed. Cambridge: Cambridge University Press, 1952. Google Scholar

[36] Forti M, Grazzini M, Nistri P, et al. Generalized Lyapunov approach for convergence of neural networks with discontinuous or non-Lipschitz activations. Phys D Nonlin Phenom, 2006, 214: 88-99 CrossRef Google Scholar

[37] Chua L O. Resistance switching memories are memristor. Appl Phys A, 2011, 102: 765-783 Google Scholar