Multi-delay dynamic neural group network global asymptotic stability and synchronization state analysis

Author

Li, Xiang ; Li, Kai

Author_Institution

Sch. of Inf. Sci. & Technol., Liaoning Univ., Shenyang, China

Volume

1

fYear

2010

fDate

27-29 March 2010

Firstpage

234

Lastpage

238

Abstract

According to a multi-delay dynamic neural group network, the Lyapunov function is constructed firstly to achieve the judgment criteria of global asymptotical stability. Then, the synchronization states are analysized based on the complex coupled network. Through the Lyapunov stability theorem, the multi-delay dependent judgment criteria of synchronization states is presented. Finally, the controller is designed based on this structure. The simulation results demonstrate the effectiveness of this controller.

Keywords

Lyapunov methods; asymptotic stability; delays; neurocontrollers; synchronisation; Lyapunov function; multidelay dependent judgment criteria; multidelay dynamic neural group network global asymptotic stability; synchronization state analysis; Artificial neural networks; Asymptotic stability; Biological system modeling; Brain modeling; Cellular neural networks; Hopfield neural networks; Lyapunov method; Neural networks; Neurons; Stability analysis; Multi-delay; globally asymptotical stability; neural group network; synchronization;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Computer Control (ICACC), 2010 2nd International Conference on

Conference_Location

Shenyang

Print_ISBN

978-1-4244-5845-5

Type

conf

DOI

10.1109/ICACC.2010.5487025

Filename

5487025