Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2017, Article ID 3273758, 10 pages
https://doi.org/10.1155/2017/3273758
Research Article

Stability Analysis for Stochastic Neutral-Type Memristive Neural Networks with Time-Varying Delay and S-Type Distributed Delays

Department of Math, Nanchang University, Nanchang, Jiangxi Province 330031, China

Correspondence should be addressed to Zuoliang Xiong; moc.361@1061gnoix

Received 5 August 2016; Accepted 9 November 2016; Published 12 February 2017

Academic Editor: Qingling Zhang

Copyright © 2017 Changjian Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. Ding and Z. Wang, “Stochastic exponential synchronization control of mem-ristive neural networks with multiple time-varying delays,” Neurocomputing, vol. 162, pp. 16–25, 2015. View at Publisher · View at Google Scholar · View at Scopus
  2. W. Wang, L. Li, H. Peng, J. Xiao, and Y. Yang, “Synchronization control of memristor-based recurrent neural networks with perturbations,” Neural Networks, vol. 53, pp. 8–14, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. H. Wang, Y. Yu, and G. Wen, “Stability analysis of fractional-order Hopfield neural networks with time delays,” Neural Networks, vol. 55, pp. 98–109, 2014. View at Publisher · View at Google Scholar · View at Scopus
  4. X. Zeng, Z. Xiong, and C. Wang, “Hopf bifurcation for neutral-type neural network model with two delays,” Applied Mathematics and Computation, vol. 282, pp. 17–31, 2016. View at Publisher · View at Google Scholar
  5. A. Wu and Z. Zeng, “Improved conditions for global exponential stability of a general class of memristive neural networks,” Communications in Nonlinear Science and Numerical Simulation, vol. 20, no. 3, pp. 975–985, 2015. View at Publisher · View at Google Scholar · View at Scopus
  6. Y. Wan and J. Cao, “Periodicity and synchronization of coupled memristive neural networks with supremums,” Neurocomputing, vol. 159, no. 1, pp. 137–143, 2015. View at Publisher · View at Google Scholar · View at Scopus
  7. G. Zhang, J. Hu, and Y. Shen, “Exponential lag synchronization for delayed memristive recurrent neural networks,” Neurocomputing, vol. 154, pp. 86–93, 2015. View at Publisher · View at Google Scholar · View at Scopus
  8. J. Xiao, S. Zhong, and Y. Li, “New passivity criteria for memristive uncertain neural networks with leakage and time-varying delays,” ISA Transactions, vol. 59, pp. 133–148, 2015. View at Publisher · View at Google Scholar · View at Scopus
  9. Y. Xin, Y. Li, Z. Cheng, and H. Xia, “Global exponential stability for switched memristive neural networks with time-varying delays,” Neural Networks, vol. 80, pp. 34–42, 2016. View at Publisher · View at Google Scholar
  10. Y. Liu, C. Li, T. Huang, and X. Wang, “Robust adaptive lag synchronization of uncertain fuzzy memristive neural networks with time-varying delays,” Neurocomputing, vol. 190, pp. 188–196, 2016. View at Publisher · View at Google Scholar
  11. X. Han, H. Wu, and B. Fang, “Adaptive exponential synchronization of memristive neural networks with mixed time-varying delays,” Neurocomputing, vol. 201, pp. 40–50, 2016. View at Publisher · View at Google Scholar
  12. L. Wang and D. Xu, “Global asymptotic stability of bidirectional associative memory neural networks with S-type distributed delays,” International Journal of Systems Science, vol. 33, no. 11, pp. 869–877, 2002. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  13. W. Han, Y. Kao, and L. Wang, “Global exponential robust stability of static interval neural networks with S-type distributed delays,” Journal of the Franklin Institute, vol. 348, no. 8, pp. 2072–2081, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  14. Z. Huang, X. Li, S. Mohamad, and Z. Lu, “Robust stability analysis of static neural network with S-type distributed delays,” Applied Mathematical Modelling, vol. 33, no. 2, pp. 760–769, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  15. G. Bao and Z. Zeng, “Global asymptotical stability analysis for a kind of discrete-time recurrent neural network with discontinuous activation functions,” Neurocomputing, vol. 193, pp. 242–249, 2016. View at Publisher · View at Google Scholar
  16. Z. Zhang, J. Cao, and D. Zhou, “Novel LMI-based condition on global asymptotic stability for a class of Cohen-Grossberg BAM networks with extended activation functions,” IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 6, pp. 1161–1172, 2014. View at Publisher · View at Google Scholar · View at Scopus
  17. L. Shi, H. Zhu, S. Zhong, and L. Hou, “Globally exponential stability for neural networks with time-varying delays,” Applied Mathematics & Computation, vol. 219, no. 21, pp. 10487–10498, 2013. View at Publisher · View at Google Scholar · View at Scopus
  18. C. Huang, P. Chen, Y. He, L. Huang, and W. Tan, “Almost sure exponential stability of delayed Hopfield neural networks,” Applied Mathematics Letters, vol. 21, no. 7, pp. 701–705, 2008. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. L. Liu and Q. Zhu, “Almost sure exponential stability of numerical solutions to stochastic delay Hopfield neural networks,” Applied Mathematics & Computation, vol. 266, pp. 698–712, 2015. View at Publisher · View at Google Scholar · View at Scopus
  20. J. Pan, X. Liu, and W. Xie, “Exponential stability of a class of complex-valued neural networks with time-varying delays,” Neurocomputing, vol. 164, pp. 293–299, 2015. View at Publisher · View at Google Scholar · View at Scopus
  21. D. Yang, G. Qiu, and C. Li, “Global exponential stability of memristive neural networks with impulse time window and time-varying delays,” Neurocomputing, vol. 171, pp. 1021–1026, 2016. View at Publisher · View at Google Scholar · View at Scopus
  22. Q. Zhu and X. Li, “Exponential and almost sure exponential stability of stochastic fuzzy delayed Cohen-Grossberg neural networks,” Fuzzy Sets & Systems, vol. 203, pp. 74–94, 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. X. Y. Lou and Q. Ye, “Input-to-state stability of stochastic memristive neural networks with time-varying delay,” Mathematical Problems in Engineering, vol. 2015, Article ID 140857, 8 pages, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  24. A. F. Filippov, “Classical solutions of differential equations with multi-valued right-hand side,” SIAM Journal on Control, vol. 5, pp. 609–621, 1967. View at Publisher · View at Google Scholar · View at MathSciNet
  25. Q. Zhu and J. Cao, “Mean-square exponential input-to-state stability of stochastic delayed neural networks,” Neurocomputing, vol. 131, pp. 157–163, 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. Y. Song, W. Sun, and F. Jiang, “Mean-square exponential input-to-state stability for neutral stochastic neural networks with mixed delays,” Neurocomputing, vol. 205, pp. 195–203, 2016. View at Publisher · View at Google Scholar