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
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;
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
DOI :
10.1109/ICARCV.2012.6485252
