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Novel global stability criteria for high-order Hopfield-type neural networks with time-varying delays
- Source :
- Journal of Mathematical Analysis and Applications. 330:144-158
- Publication Year :
- 2007
- Publisher :
- Elsevier BV, 2007.
-
Abstract
- This paper discusses a generalized model of high-order Hopfield-type neural networks with time-varying delays. Some novel global stability criteria of the system is derived by using Lyapunov method, linear matrix inequality (LMI) and analytic technique. The LMI-based criteria obtained here are computationally more flexible and more generic than many other existing criteria. A numerical example is given to illustrate our result.
- Subjects :
- Lyapunov function
Artificial neural network
Applied Mathematics
Time-varying delays
Stability (learning theory)
Linear matrix inequality
Type (model theory)
symbols.namesake
Computer Science::Systems and Control
symbols
Applied mathematics
High order
Stability
Algorithm
High-order Hopfield-type neural networks
Analysis
Matrix method
Delay time
Mathematics
Subjects
Details
- ISSN :
- 0022247X
- Volume :
- 330
- Database :
- OpenAIRE
- Journal :
- Journal of Mathematical Analysis and Applications
- Accession number :
- edsair.doi.dedup.....8ce36341aa991c475fc28ec64072c300
- Full Text :
- https://doi.org/10.1016/j.jmaa.2006.07.058