DocumentCode
724245
Title
Passivity analysis of neural networks with discrete and distributed delays
Author
Wei Wang ; Hongbing Zeng ; Shenping Xiao
Author_Institution
Hunan Railway Prof. Technol. Coll., Zhuzhou, China
fYear
2015
fDate
23-25 May 2015
Firstpage
2894
Lastpage
2898
Abstract
This study is concerned with the problem of delay-dependent passivity analysis for neural networks with discrete and distributed delays. By employing a new integral inequality and the convex combination approach to estimate the derivative of Lyapunov-Krasovskii functional, sufficient conditions are established to ensure that the considered neural network is passive. A given numerical example demonstrates the effectiveness of the proposed method.
Keywords
Lyapunov methods; convex programming; delays; discrete systems; estimation theory; neurocontrollers; Lyapunov-Krasovskii functional; convex combination approach; derivative estimation; discrete delay; distributed delay; integral inequality; neural network; passivity analysis; Asymptotic stability; Biological neural networks; Delays; Stability criteria; Symmetric matrices; Delay-dependent; Lyapunov-Krasovskii functional; Neural networks; Passivity;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location
Qingdao
Print_ISBN
978-1-4799-7016-2
Type
conf
DOI
10.1109/CCDC.2015.7162420
Filename
7162420
Link To Document