DocumentCode :
3576051
Title :
Delay-dependent passivity analysis for Markov jump neural networks with time-varying delays
Author :
Jing Wang ; Hao Shen
Author_Institution :
Sch. of Electr. & Inf. Eng., Anhui Univ. of Technol., Ma´anshan, China
fYear :
2014
Firstpage :
1530
Lastpage :
1533
Abstract :
This paper addresses the passivity analysis problem for Markov jump neural networks with time-varying delays. The aim is focus on establishing the passivity condition of the considered neural networks. To reduce the conservatism of the proposed passivity condition, based on an extended Wirtinger inequality, a reciprocally convex approach is used. A numerical example is presented to show effectiveness of our proposed condition.
Keywords :
Markov processes; convex programming; delays; neurocontrollers; time-varying systems; Markov jump neural networks; delay-dependent passivity analysis; extended Wirtinger inequality; reciprocally convex approach; time-varying delays; Biological neural networks; Delays; Linear matrix inequalities; Markov processes; Neurons; Symmetric matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Control (ICMC), 2014 International Conference on
Print_ISBN :
978-1-4799-2537-7
Type :
conf
DOI :
10.1109/ICMC.2014.7231815
Filename :
7231815
Link To Document :
بازگشت