Stability of Cohen-Grossberg neural networks with time-varying delays.
In this paper, we investigate the existence and stability of the equilibrium point of Cohen-Grossberg neural networks with time-varying delays. Under easily verified conditions, exponential stability is obtained when the delay is finite, while asymptotic stability is obtained when the delay is infinite. Moreover, the stability obtained is robust. The only condition for the delay term is continuity. The results obtained here improve and extend to those in the literature.
Huang
Tingwen
T
Texas A&M University at Qatar, c/o Qatar Foundation, PO Box 5825, Doha, Qatar. tingwen.huang@qatar.tamu.edu
Chan
Andrew
A
Huang
Yu
Y
Cao
Jinde
J
D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D016247:Information Storage and Retrieval; D008390:Markov Chains; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes; D013598:Systems Theory; D013997:Time Factors