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Improved Global Robust Stability for Interval-Delayed Hopfield Neural Networks

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Abstract

A modified form of a recent criterion for the global robust stability of interval-delayed Hopfield neural networks is presented. The effectiveness of the modified criterion is demonstrated with the help of an example.

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References

  1. Liao X, Yu J (1998) Robust stability for interval Hopfield neural networks with time delay. IEEE Trans Neural Netw 9: 1042–1045

    Article  Google Scholar 

  2. Liao X, Wong K, Wu Z, Chen G (2001) Novel robust stability for interval-delayed Hopfield neural net-works. IEEE Trans Ciruits Syst I 48: 1355–1359

    Article  MATH  MathSciNet  Google Scholar 

  3. Arik S (2003) Global robust stability of delayed neural networks. IEEE Trans Ciruits Syst I 50: 156–160

    Article  MathSciNet  Google Scholar 

  4. Sun CY, Feng CB (2003) Global robust exponential stability of interval neural networks with delays. Neural Process Lett 17: 107–115

    Article  Google Scholar 

  5. Sun CY, Feng CB (2004) On robust exponential periodicity of interval neural networks with delays. Neural Process Lett 20: 53–61

    Article  Google Scholar 

  6. Cao J, Chen T (2004) Globally exponentially robust stability and periodicity of delayed neural networks. Chaos Solitons Fractals 22: 957–963

    Article  MATH  MathSciNet  Google Scholar 

  7. Cao J, Huang DS, Qu Y (2005) Global robust stability of delayed recurrent neural networks. Chaos Solitons Fractals 23: 221–229

    Article  MATH  MathSciNet  Google Scholar 

  8. Cao J, Wang J (2005) Global asymptotic and robust stability of recurrent neural networks with time delays. IEEE Trans Ciruits Syst I 52: 417–426

    Article  MathSciNet  Google Scholar 

  9. Singh V (2005) Global robust stability of delayed neural networks: An LMI approach. IEEE Trans Circuits Syst II 52: 33–36

    Article  Google Scholar 

  10. Singh V (2005) A novel global robust stability criterion for neural networks with delay. Phys Lett A 337: 369–373

    Article  MATH  ADS  Google Scholar 

  11. Li C, Liao X, Zhang R, Prasad A (2005) Global robust exponential stability analysis for interval neural networks with time-varying delays. Chaos Solitons Fractals 25: 751–757

    Article  MATH  Google Scholar 

  12. He Y, Wang QG, Zheng WX (2005) Global robust stability for delayed neural networks with polytopic type uncertainties. Chaos Solitons Fractals 26: 1349–1354

    Article  MATH  MathSciNet  Google Scholar 

  13. Xu S, Lam J, Ho DWC (2005) Novel global robust stability criteria for interval neural networks with multiple time-varying delays. Phys Lett A 342: 322–330

    Article  ADS  Google Scholar 

  14. Ozcan N, Arik S (2006) Global robust stability analysis of neural networks with multiple time delays. IEEE Trans Ciruits Syst I 53: 166–176

    Article  MathSciNet  Google Scholar 

  15. Ding K, Huang NJ (2006) Global robust exponential stability of interval general BAM neural network with delays. Neural Process Lett 23: 171–182

    Article  Google Scholar 

  16. Singh V (2007) Improved global robust stability criterion for delayed neural networks. Chaos Solitons Fractals 31: 224–229

    Article  MATH  MathSciNet  Google Scholar 

  17. Li C, Chen J, Huang T (2007) A new criterion for global robust stability of interval neural networks with discrete time delays. Chaos Solitons Fractals 31: 561–570

    Article  MATH  MathSciNet  Google Scholar 

  18. Singh V (2007) Global robust stability of delayed neural networks: Estimating upper limit of norm of delayed connection weight matrix. Chaos Solitons Fractals 32: 259–263

    Article  MATH  MathSciNet  Google Scholar 

  19. Wang L, Gao Y (2006) Global exponential robust stability of reaction-diffusion interval neural networks with time-varying delays. Phys Lett A 350: 342–348

    Article  ADS  MathSciNet  Google Scholar 

  20. Qi H (2007) New sufficient conditions for global robust stability of delayed neural networks. IEEE Trans Ciruits Syst I 54: 1131–1141

    Article  Google Scholar 

  21. Ding K, Huang NJ, Xu X (2007) Global robust exponential stability of interval BAM neural network with mixed delays under uncertainty. Neural Process Lett 25: 127–141

    Article  Google Scholar 

  22. Singh V (2007) On global robust stability of interval Hopfield neural networks with delay. Chaos Solitons Fractals 33: 1183–1188

    Article  MATH  MathSciNet  Google Scholar 

  23. Singh V (2007) Novel LMI condition for global robust stability of delayed neural networks. Chaos Solitons Fractals 34: 503–508

    Article  MATH  MathSciNet  Google Scholar 

  24. Zhang Q, Ma R, Wang C, Xu J (2003) On the global stability of delayed neural networks. IEEE Trans Autom Cont 48: 794–797

    Article  MathSciNet  Google Scholar 

  25. Zhang Q, Wei X, Xu J (2003) Global asymptotic stability of Hopfield neural networks with transmission delays. Phys Lett A 318: 399–405

    Article  MATH  ADS  MathSciNet  Google Scholar 

  26. Cao J, Wang J (2003) Global asymptotic stability of recurrent neural networks with Lipschitz-continuous activation functions and time-varying delays. IEEE Trans Ciruits Syst I 50: 33–44

    MathSciNet  Google Scholar 

  27. Arik S (2003) Global asymptotic stability of a larger class of neural networks with constant time delays. Phys Lett A 311: 504–511

    Article  MATH  ADS  Google Scholar 

  28. Lu W, Rong L, Chen T (2003) Global convergence of delayed neural network systems. Int J Neural Syst 13: 193–204

    Article  Google Scholar 

  29. Qi HD, Qi L (2004) Deriving sufficient conditions for global asymptotic stability of delayed neural networks via nonsmooth analysis. IEEE Trans Neural Netw 15: 99–109

    Article  Google Scholar 

  30. Singh V (2004) A generalized LMI-based approach to the global asymptotic stability of delayed cellular neural networks. IEEE Trans Neural Netw 15: 223–225

    Article  Google Scholar 

  31. Singh V (2004) Robust stability of cellular neural networks with delay: Linear matrix inequality approach. IEE Proc Contr Theor Appl 151: 125–129

    Article  Google Scholar 

  32. Qi HD, Qi L (2005) Deriving sufficient conditions for global asymptotic stability of delayed neural networks via nonsmooth analysis II. IEEE Trans Neural Netw 16: 1701–1706

    Article  Google Scholar 

  33. Xu S, Lam J, Ho DWC, Zou Y (2005) Improved global robust asymptotic stability criteria for delayed cellular neural networks. IEEE Trans Syst Man Cybern B 35: 1317–1321

    Article  Google Scholar 

  34. He Y, Wu M, She JH (2006) An improved global asymptotic stability criterion for delayed cellular neural networks. IEEE Trans Neural Netw 17: 250–252

    Article  Google Scholar 

  35. Rong L, Chen T (2006) New results on the robust stability of Cohen-Grossberg neural networks with delays. Neural Process Lett 24: 193–202

    Article  MATH  Google Scholar 

  36. Liu H, Chen G (2007) Delay-dependent stability for neural networks with time-varying delay. Chaos Solitons Fractals 33: 171–177

    Article  MathSciNet  Google Scholar 

  37. Lu W, Chen T (2007) R n+ - global stability of a Cohen–Grossberg neural network system with nonnegative equilibria. Neural Netw 20: 714–722

    Article  MATH  Google Scholar 

  38. Lu W, Chen T (2005) Dynamical behaviors of Cohen–Grossberg neural networks with discontinuous activation functions. Neural Netw 18: 231–242

    Article  MATH  Google Scholar 

  39. Zhang Q, Wei X, Xu J (2007) Stability of delayed cellular neural networks. Chaos Solitons Fractals 31: 514–520

    Article  MATH  MathSciNet  Google Scholar 

  40. Zhang Q, Wei X, Xu J (2007) Delay-dependent global stability results for delayed Hopfield neural networks. Chaos Solitons Fractals 34: 662–668

    Article  MATH  MathSciNet  Google Scholar 

  41. Zhang Q, Wei X, Xu J (2007) A new global stability result for delayed neural networks. Nonlinear Anal Real World Appl 8: 1024–1028

    Article  MATH  MathSciNet  Google Scholar 

  42. Yu W, Cao J (2007) Robust control of uncertain stochastic recurrent neural networks with time-varying delay. Neural Process Lett 26: 101–119

    Article  Google Scholar 

  43. Song Q-K, Cao J-D (2007) Robust stability in Cohen-Grossberg neural network with both time-varying and distributed delays. Neural Process Lett. doi:10.1007/s11063-007-9068-3

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Authors and Affiliations

  1. Department of Electrical-Electronics Engineering, Atilim University, Ankara, 06836, Turkey

    Vimal Singh

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  1. Vimal Singh
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Correspondence to Vimal Singh.

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Singh, V. Improved Global Robust Stability for Interval-Delayed Hopfield Neural Networks. Neural Process Lett 27, 257–265 (2008). https://doi.org/10.1007/s11063-008-9074-0

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  • DOI: https://doi.org/10.1007/s11063-008-9074-0

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