Title :
Periodicity of reaction-diffusion Cohen-Grossberg neural networks with time-varying delays
Author_Institution :
Coll. of Math. & Syst. Sci., Xinjiang Univ., Urumqi
Abstract :
In this paper, we study reaction-diffusion Cohen-Grossberg neural networks with time-varying delays. Under the Dirichlet boundary condition, by constructing Lyapunov functional method, some sufficient conditions are given to ensure the exponential stability of the periodic solution. Finally, a numerical example is given to verify the theoretical analysis.
Keywords :
Lyapunov methods; asymptotic stability; boundary-value problems; delay systems; neural nets; reaction-diffusion systems; time-varying systems; Dirichlet boundary condition; Lyapunov functional method; exponential stability; periodic solution; reaction-diffusion Cohen-Grossberg neural networks; time-varying delays; Boundary conditions; Computer applications; Delay effects; Educational institutions; Mathematics; Neural networks; Neurons; Stability; Sufficient conditions; Time varying systems;
Conference_Titel :
Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3530-2
Electronic_ISBN :
978-1-4244-3531-9
DOI :
10.1109/KAMW.2008.4810527
