DocumentCode
596615
Title
New LMI-based criteria for global robust stability of neural networks with time-varying delays
Author
Zhenhua Huang ; Bangrong Li
Author_Institution
Coll. of Math. & Stat., Hubei Normal Univ., Huangshi, China
fYear
2012
fDate
18-20 Oct. 2012
Firstpage
418
Lastpage
422
Abstract
In this paper, some sufficient conditions for global robust asymptotical stability of neural networks with time-varying delays are presented. On basis of the obtained results, some linear matrix inequality (LMI) criteria are derived. A comparison of the present criteria with the previous criteria is made. Moreover, an example is given to show the effectiveness of the obtained results.
Keywords
asymptotic stability; delays; linear matrix inequalities; neural nets; robust control; time-varying systems; LMI-based criteria; global robust asymptotical stability; linear matrix inequality criteria; neural networks; sufficient conditions; time-varying delays; Asymptotic stability; Biological neural networks; Delay; Neurons; Robust stability; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4673-1743-6
Type
conf
DOI
10.1109/ICACI.2012.6463197
Filename
6463197
Link To Document