DocumentCode
1662459
Title
Robust stability with general decay rate for stochastic neural networks with unbounded time-varying delays
Author
Fuke Wu ; Shigeng Hu
Author_Institution
Sch. of Math. & Stat., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear
2012
Firstpage
753
Lastpage
758
Abstract
This paper considers a class of stochastic neural networks with unbounded time-varying delays and establishes the mean square and almost sure stability with general decay rate and their robustness. This stability may be specialized as the classical exponential stability and polynomial stability.
Keywords
Hopfield neural nets; asymptotic stability; delays; mean square error methods; polynomials; stochastic processes; time-varying systems; Hopfield neural networks; almost sure stability; classical exponential stability; general decay rate; mean square stability; polynomial stability; robust stability; stochastic neural networks; unbounded time-varying delays; Biological neural networks; Control theory; Delays; Stability criteria; General decay rate; Robustness; Stability; Stochastic neural networks; Time-varying delays;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4673-1871-6
Electronic_ISBN
978-1-4673-1870-9
Type
conf
DOI
10.1109/ICARCV.2012.6485252
Filename
6485252
Link To Document