Title :
Stability Analysis of Stochastic Neural Networks with Time-Varying Delays
Author :
Zhao, Zhenjiang ; Song, Qiankun
Author_Institution :
Dept. of Math., Huzhou Teachers Coll., Huzhou, China
Abstract :
In this paper, the global asymptotic stability is investigated for a class of stochastic neural networks with time-varying delay and generalized activation functions. By constructing appropriate Lyapunov-Krasovskii functional, and employing the free-weighting matrix method and stochastic analysis technique, a delay-dependent criterion for checking the global asymptotic stability of the addressed neural networks is established in terms of linear matrix inequalities (LMIs), which can be solved easily by using the effective LMI toolbox in MATLAB.
Keywords :
Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; stochastic systems; LMI toolbox; Lyapunov-Krasovskii functional; MATLAB; delay-dependent criterion; free-weighting matrix method; generalized activation function; global asymptotic stability; linear matrix inequalities; stability analysis; stochastic analysis technique; stochastic neural network; time-varying delay; Artificial neural networks; Asymptotic stability; Biological neural networks; Delay; Stability criteria; Stochastic processes;
Conference_Titel :
Intelligent Systems and Applications (ISA), 2011 3rd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9855-0
Electronic_ISBN :
978-1-4244-9857-4
DOI :
10.1109/ISA.2011.5873438
