Title :
Exponential stability of stochastic interval neural networks with multi-delay
Author :
Han, Jin-fang ; Wang, Shu-tian ; Ma, Qin
Author_Institution :
Coll. of Sci., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Abstract :
Globally exponential stability of a class of stochastic interval neural networks with delays are analyzed via the method of Lyapunov function and norm inequalities, Itô formula and Razumikhin theorems. several simple sufficient criteria of its global exponential stability had been given. some recent results reported in the literature are extend. four kinds of equivalent description of the stochastic interval matrix is also introduced.
Keywords :
Lyapunov methods; asymptotic stability; delays; matrix algebra; neural nets; stochastic processes; Itô formula; Lyapunov function; Razumikhin theorems; exponential stability; multidelay; norm inequalities; stochastic interval matrix; stochastic interval neural networks; Asymptotic stability; Circuit stability; Delay; Neural networks; Stability criteria; Stochastic processes; Delays; Exponential stability; Itô formula; Lyapunov function; Stochastic interval neural networks;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4577-0305-8
DOI :
10.1109/ICMLC.2011.6016808
