TY - JOUR

T1 - Controlled synchronization in two hybrid FitzHugh-Nagumo systems

AU - Plotnikov, Sergei A.

AU - Fradkov, Alexander L.

PY - 2016

Y1 - 2016

N2 - We study synchronization in two FitzHugh-Nagumo systems with discrete coupling, which are the simplest model of neural network. It is well known that High delays in propagation between the nodes hinder synchronization. We use the linear matrix inequality method to study the impact of the discretization step on the system synchronization. We show that external stimulus can be used for controlling synchrony in the case of its absence. We develop the algorithm for synchronization of FitzHugh-Nagumo systems and find the conditions of its applicability. The simulation results confirm the efficiency of suggested algorithm. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All right reserved.

AB - We study synchronization in two FitzHugh-Nagumo systems with discrete coupling, which are the simplest model of neural network. It is well known that High delays in propagation between the nodes hinder synchronization. We use the linear matrix inequality method to study the impact of the discretization step on the system synchronization. We show that external stimulus can be used for controlling synchrony in the case of its absence. We develop the algorithm for synchronization of FitzHugh-Nagumo systems and find the conditions of its applicability. The simulation results confirm the efficiency of suggested algorithm. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All right reserved.

KW - Hybrid models

KW - Oscillation

KW - Neural dynamics

KW - Synchronization control

U2 - 10.1016/j.ifacol.2016.07.998

DO - 10.1016/j.ifacol.2016.07.998

M3 - статья

VL - 49

SP - 137

EP - 141

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 14

Y2 - 29 June 2016 through 1 July 2016

ER -