Title :
Exponential Stability of Stochastic Fuzzy Recurrent Neural Networks with Time-Varying Delays and Diffusion Terms
Author_Institution :
Dept. of Math. & Phys., Wuhan Univ. of Sci. & Eng., Wuhan, China
Abstract :
In this paper, the problem on stability analysis of stochastic fuzzy recurrent neural networks with time-varying delays and reaction-diffusion terms is considered. Without requiring the delay functions are differential, the sufficient conditions are derived to guarantee the mean square exponential stability of an equilibrium solution.
Keywords :
asymptotic stability; delays; fuzzy neural nets; recurrent neural nets; stochastic processes; fuzzy neural networks; mean square exponential stability; reaction-diffusion terms; recurrent neural networks; stochastic networks; time-varying delays; Biological neural networks; Delay; Extraterrestrial measurements; Fuzzy logic; Fuzzy neural networks; Neurotransmitters; Recurrent neural networks; Stability analysis; Stability criteria; Stochastic processes;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.140
