New LMI conditions for global exponential stability of cellular neural networks with delays

Nonlinear Analysis: Real World Applications

Volumn 10, Issue 1, 2009, Pages 287-297

  Chen, Ling ^a,b   Zhao, Hongyong ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b JINLING INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Equilibrium point; Global exponential stability; Linear matrix inequality

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS; COMPUTER SIMULATION; LINEAR CONTROL SYSTEMS; LINEAR MATRIX INEQUALITIES; MATRIX ALGEBRA; THEOREM PROVING; TIME VARYING NETWORKS;

CELLULAR NEURAL NETWORKS; EQUILIBRIUM POINT; GLOBAL EXPONENTIAL STABILITY; LINEAR MATRIX INEQUALITY;

NEURAL NETWORKS;

EID: 50349099931     PISSN: 14681218     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.nonrwa.2007.09.011     Document Type: Article

References (12)

1. Chua L.O., and Yang L. Cellular neural networks: Theory and applications. IEEE Transactions on Circuits and Systems I 35 (1988) 1257-1290
2. Lu W., Rong L., and Chen T. Global convergence of delayed neural network systems. International Journal of Neural Systems 13 (2003) 1-12
3. Huang H., and Cao J. Exponential stability analysis of uncertain stochastic neural networks with multiple delays. Nonlinear Analysis: Real World Applications 8 (2007) 646-653
4. Park J.H. Global exponential stability of cellular neural networks with variable delays. Applied Mathematics and Computation 183 (2006) 1214-1219
5. Gau R., Lien C., and Hsieh J. Global exponential stability for uncertain cellular neural networks with multiple time-varying delays via LMI approach. Chaos, Solitons and Fractals 32 (2007) 1258-1267
6. Zhao H., and Cao J. New conditions for global exponential stability of cellular neural networks with delays. Neural Networks 18 (2005) 1332-1340
7. Park J.H. A new stability analysis of delayed cellular neural networks. Applied Mathematics and Computation 181 (2006) 200-205
8. Lou X., and Cui B. New LMI conditions for delay-dependent asymptotic stability of delayed Hopfield neural networks. Neucomputing 69 (2006) 2374-2378
9. Lou X., and Cui B. Comments and further improvements on "New LMI conditions for delay-dependent asymptotic stability of delayed Hopfield neural networks". Neucomputing 70 (2007) 2566-2571
10. Forti M., and Tesi A. New conditions for global stability of neural networks with application to linear and quadratic programming problems. IEEE Transactions on Circuits and Systems I 42 (1995) 354-365
11. Sanchez E.N., and Perez J.P. Input-to-state stability (ISS) analysis for dynamic NN. IEEE Transactions on Circuits and Systems I 46 (1999) 1395-1398
12. Boyd S., et al. Linear Matrix Inequations in System and Control Theory (1994), SIAM, Philadelphia, PA