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
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;
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
DOI :
10.1109/ICACI.2012.6463197
