Some improved criteria for global robust exponential stability of neural networks with time-varying delays

Communications in Nonlinear Science and Numerical Simulation

Volumn 15, Issue 12, 2010, Pages 3782-3794

  Shao, Jin Liang ^a   Huang, Ting Zhu ^a   Zhou, Sheng ^a  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

Global robust exponential stability; Halanay inequality; Interval neural networks; Linear matrix inequality; Nonnegative matrix; Time varying delays

Indexed keywords

ASYMPTOTIC STABILITY; NEURAL NETWORKS; ROBUSTNESS (CONTROL SYSTEMS); STABILITY CRITERIA; TIME DELAY; TIME VARYING CONTROL SYSTEMS; TIME VARYING NETWORKS;

CONDITION; GLOBAL ROBUST EXPONENTIAL STABILITIES; HALANAY INEQUALITY; INTERVAL NEURAL NETWORK; LINEAR MATRIX IN EQUALITIES; NEURAL-NETWORKS; NON-NEGATIVE MATRIX; TIME-VARYING DELAY;

LINEAR MATRIX INEQUALITIES;

EID: 77952743829     PISSN: 10075704     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cnsns.2010.02.002     Document Type: Article

References (30)

1. Arik S., and Tavsanoglu V. On the global asymptotic stability of delayed cellular neural networks. IEEE Trans Circuits Syst I, Fundam Theory Appl 47 (2000) 571-574
2. Chen T. Global convergence of delayed dynamical system. IEEE Trans Neural Networks 12 (2001) 1532-1536
3. Peng J., Qiao H., and Xu Z. A new approach to stability of neural networks with time-varying delays. Neural Networks 15 (2002) 95-103
4. Zhang J. Globally exponential stability of neural networks with variable delays. IEEE Trans Circuits Syst I, Fundam Theory Appl 50 (2003) 288-291
5. Huang H., Ho D.W.C., and Cao J. Analysis of global exponential stability and periodic solutions of neural networks with time-varing delays. Neural Networks 18 (2005) 161-170
6. Yuan K., and Cao J. An analysis of global asymptotic stability of delayed Cohen-Grossberg neural networks via nonsmooth analysis. IEEE Trans Circuits Syst I, Reg Papers 52 9 (2005) 1854-1861
7. Huang L., Huang C., and Liu B. Dynamics of a class of cellular neural networks with time-varying delays. Phys Lett A 345 (2005) 330-344
8. Huang H., Cao J., and Qu Y. Global robust stability of delayed neural networks with a class of general activation functions. J Comput Syst Sci 69 (2004) 688-700
9. Sun C., and Feng C. Global robust exponential stability of interval neural networks with delays. Neural Process Lett 17 (2003) 107-115
10. Cao J., and Chen T. Global exponentially robust stability and periodicity of delayed neural networks. Chaos Solitons Fract 22 (2004) 957-963
11. Chen T., and Rong L. Robust global exponential stability of Cohen-Grossberg neural networks with time delays. IEEE Trans Neural Networks 15 1 (2004) 203-206
12. Cao J., Huang D., and Qu Y. Global robust stability of delayed recurrent neural networks. Chaos Solitons Fract 23 (2005) 221-229
13. Arik S. Global robust stability analysis of neural networks with discrete time delays. Chaos Solitons Fract 26 (2005) 1407-1414
14. Cao J., and Wang J. Global asymptotic and robust stability of recurrent neural networks with time delays. IEEE Trans Circuits Syst I, Fundam Theory Appl 52 2 (2005) 417-426
15. Chen A., Cao J., and Huang L. Global robust stability of interval cellular neural networks with time-varying delays. Chaos Solitons Fract 23 (2005) 787-799
16. Ozcan N., and Arik S. An analysis of global robust stability of neural networks with discrete time delays. Phys Lett A 359 (2006) 445-450
17. Ozcan N., and Arik S. Global robust stability analysis of neural networks with multiple time delays. IEEE Trans Circuits Syst I, Reg Papers 53 1 (2006) 166-176
18. Zhang J. Global exponential stability of interval neural networks with variable delays. Appl Math Lett 19 (2006) 1222-1227
19. Singh V. Global robust stability of delayed neural networks: estimating upper limit of norm of delayed connection weight matrix. Chaos Solitons Fract 32 (2007) 259-263
20. Singh V. On global robust stability of interval Hopfield neural networks with delay. Chaos Solitons Fract 33 4 (2007) 1183-1188
21. Qi H. New sufficient conditions for global robust stability of delayed neural networks. IEEE Trans Circuits Syst I, Reg Papers 54 5 (2007) 1131-1141
22. Yu W., and Yao L. Global robust stability of neural networks with time varying delays. J Comput Appl Math 206 2 (2007) 679-687
23. Zhang H., Wang Z., and Liu D. Robust exponential stability of recurrent neural networks with multiple time-varying delays. IEEE Trans Circuits Syst II: Exp Briefs 54 8 (2007) 730-734
24. Shen T., and Zhang Y. Improved global robust stability criteria for delayed neural networks. IEEE Trans Circuits Syst II: Exp Briefs 54 8 (2007) 715-719
25. Singh V. Improved global robust stability for interval-delayed hopfield neural networks. Neural Process Lett 27 3 (2008) 257-265
26. Singh V. Improved global robust stability of interval delayed neural networks via split interval: generalizations. Appl Math Comput 206 1 (2008) 290-297
27. Shao J., and Huang T. A note on global robust stability criteria for interval delayed neural networks via an LMI approach. IEEE Trans Circuits Syst II: Exp Briefs 55 (2008) 1198-1202
28. Gahinet P., Nemirovski A., Laub A.J., and Chilali M. LMI control toolbox-for use with Matlab (1995), The Math Works Inc., Natick (MA)
29. Horn R.A., and Johnson C.R. Matrix analysis (1986), Cambridge University Press, Cambridge (MA)
30. Zhou D., and Cao J. Globally exponential stability conditions for cellular neural networks with time-varying delays. Appl Math Comput 131 (2002) 487-496