DocumentCode
527557
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
Volume
2
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
782
Lastpage
784
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-5958-2
Type
conf
DOI
10.1109/ICNC.2010.5583205
Filename
5583205
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