title: Robust synchronization of delayed chaotic FitzHugh-Nagumo neurons under external electrical stimulation.
abstract: Synchronization of chaotic neurons under external electrical stimulation (EES) is studied in order to understand information processing in the brain and to improve the methodologies employed in the treatment of cognitive diseases. This paper investigates the dynamics of uncertain coupled chaotic delayed FitzHugh-Nagumo (FHN) neurons under EES for incorporated parametric variations. A global nonlinear control law for synchronization of delayed neurons with known parameters is developed. Based on local and global Lipschitz conditions, knowledge of the bounds on the neuronal states, the Lyapunov-Krasovskii functional, and the L(2) gain reduction, a less conservative local robust nonlinear control law is formulated to address the problem of robust asymptotic synchronization of delayed FHN neurons under parametric uncertainties. The proposed local control law guarantees both robust stability and robust performance and provides the L(2) bound for uncertainty rejection in the synchronization error dynamics. Separate conditions for single-input and multiple-input control schemes for synchronization of a wide class of FHN systems are provided. The results of the proposed techniques are verified through numerical simulations.
authors.affiliation: Department of Electrical Engineering, Pakistan Institute of Engineering and Applied Sciences (PIEAS), P.O. Box 45650, Islamabad, Pakistan.
authors.forename: Muhammad
authors.initials: M
authors.lastname: Rehan
authors.forename: Keum-Shik
authors.initials: KS
authors.lastname: Hong
mesh_terms: D000465:Algorithms; D001921:Brain / Q000378:metabolism; D003072:Cognition Disorders / Q000503:physiopathology; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D004558:Electric Stimulation; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D015233:Models, Statistical; D009474:Neurons / Q000378:metabolism*; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted