title: Stability of Cohen-Grossberg neural networks with time-varying delays.
abstract: 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.
authors.affiliation: Texas A&M University at Qatar, c/o Qatar Foundation, PO Box 5825, Doha, Qatar. tingwen.huang@qatar.tamu.edu
authors.forename: Tingwen
authors.initials: T
authors.lastname: Huang
authors.forename: Andrew
authors.initials: A
authors.lastname: Chan
authors.forename: Yu
authors.initials: Y
authors.lastname: Huang
authors.forename: Jinde
authors.initials: J
authors.lastname: Cao
mesh_terms: 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