DocumentCode
1679684
Title
Robust stability for neural networks of neutral-type with mixed time-delays
Author
Zhu, Qingyu ; Zhou, Wuneng ; Mou, Xiaozheng
Author_Institution
Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
fYear
2010
Firstpage
2668
Lastpage
2673
Abstract
In this paper, the robust stability is investigated for neural networks of neutral-type with both discrete and distributed time-varying delays. Based on Lyapunov-Krasovskii stability theory and stochastic analysis approaches, several new criteria are derived to guarantee the robust stability of the system. Some numerical examples are given to demonstrate the applicability of our proposed stability criteria.
Keywords
delays; neurocontrollers; robust control; stochastic processes; Lyapunov-Krasovskii stability theory; discrete time-varying delays; distributed time-varying delays; mixed time-delays; neural networks; robust stability; stochastic analysis; Artificial neural networks; Asymptotic stability; Delay; Numerical stability; Robust stability; Stability criteria; Symmetric matrices; discrete and distributed time-delays; neural networks; neutral-type; robust stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location
Jinan
Print_ISBN
978-1-4244-6712-9
Type
conf
DOI
10.1109/WCICA.2010.5554143
Filename
5554143
Link To Document