title: Exponential stabilization of neural networks with various activation functions and mixed time-varying delays.
abstract: This paper presents some results on the global exponential stabilization for neural networks with various activation functions and time-varying continuously distributed delays. Based on augmented time-varying Lyapunov-Krasovskii functionals, new delay-dependent conditions for the global exponential stabilization are obtained in terms of linear matrix inequalities. A numerical example is given to illustrate the feasibility of our results.
authors.affiliation: Institute of Mathematics, Vietnam Academy of Science and Technology, Hanoi 10307, Vietnam. vnphat@math.ac.vn
authors.forename: V N
authors.initials: VN
authors.lastname: Phat
authors.forename: H
authors.initials: H
authors.lastname: Trinh
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors