Title :
Novel criteria on global exponential stability of fuzzy Cohen-Grossberg neural networks with time-varying delay
Author :
Kim, Yongsu ; Zhang, Huaguang ; Xin Zhang ; Cui, Lili
Author_Institution :
Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
Global exponential stability problem of the fuzzy Cohen-Grossberg neural networks (FCGNNs) with time-varying delay is considered in this paper. By using the Lyapunov-Krasovskii method, the novel sufficient conditions are obtained to guarantee the global exponential stability of the considered system. These conditions are expressed in the terms of linear matrix inequalities (LMIs), and can be checked by resorting to the Matlab LMI Toolbox. Finally, a numerical example is given to show the effectiveness of the obtained results.
Keywords :
Lyapunov methods; asymptotic stability; delays; fuzzy neural nets; linear matrix inequalities; Lyapunov-Krasovskii method; Matlab LMI Toolbox; fuzzy Cohen-Grossberg neural network; global exponential stability; linear matrix inequalities; time-varying delay; Cellular neural networks; Delay effects; Fuzzy neural networks; Fuzzy sets; Linear matrix inequalities; Neural networks; Neurofeedback; Stability criteria; State feedback; Sufficient conditions; Delay-dependent; Fuzzy Cohen-Grossberg neural networks; Global exponential stability; Linear matrix inequality (LMI); Time-varying Delay;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
DOI :
10.1109/CCDC.2009.5191977
