Journal
NEUROCOMPUTING
Volume 74, Issue 1-3, Pages 265-273Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2010.03.020
Keywords
Delayed neural networks; Exponential synchronization; Free weighting matrix approach; Linear matrix inequality (LMI)
Categories
Funding
- National Science Foundation [60425310]
- National Natural Science Foundation of China [60974026]
- Program for New Century Excellent Talents in University [NCET-06-0679]
- National Science Fund for Distinguished Youth Scholars of Hunan Province [08JJ1010]
- Research Fund for the Doctoral Program of Higher Education of China [200805330004]
- Innovation Foundation of Central South University
Ask authors/readers for more resources
This paper investigates the problem of exponential synchronization for neural networks with mixed delays using sampled-data feedback control Lyapunov-Krasovskii functional combining with the input delay approach as well as the Improved free-weighting matrix approach are employed to derive several sufficient criteria ensuring the delayed neural networks to be exponentially synchronous The conditions obtained are dependent not only on the maximum sampling interval but also on the exponential synchronization rate A numerical example is given to demonstrate the usefulness and merits of the proposed scheme (C) 2010 Elsevier B V All rights reserved
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
