Title :
New asymptotical stability conditions for delayed neural networks model with distribution
Author :
Liu, Haifei ; Wu, Chengyao ; Li, Xindan ; Zhu, Hongliang
Author_Institution :
Sch. of Manage. & Eng., Nanjing Univ., Nanjing, China
Abstract :
In this Letter, based on homeomorphism function and the Lyapunov functional method, we discuss the globally asymptotical stability of periodic solutions for a class of memory neural networks with variable coefficients, delays and distribution. And new sufficient conditions are given. Additionally,one example is also worked out to illustrate practicability and effectiveness of the conditions. The results extend and improve the earlier publications.
Keywords :
Lyapunov methods; asymptotic stability; delays; neural nets; Lyapunov functional method; asymptotical stability conditions; delayed neural networks model; delays; globally asymptotical stability; homeomorphism function; memory neural networks; periodic solutions; sufficient conditions; Artificial neural networks; Asymptotic stability; Circuit stability; Delay; Differential equations; Stability criteria;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583205
