Chaos Synchronization of Coupled FitzHugh-Nagumo Neurons Via Adaptive Sliding Mode Control

In this paper, an adaptive neural network (NN) sliding mode controller is proposed to realize the chaos synchronization of two gap junction coupled FitzHugh-Nagumo (FHN) neurons under external electrical stimulation. The controller consists of two simple radial basis function (RBF) NNs which are use...

Full description

Saved in:
Bibliographic Details
Main Authors: Yan-Qiu Che, Shi-Gang Cui, Jiang Wang, Bin Deng, Xi-Le Wei
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Chaos
Chaos synchronization
Electrical stimulation
FitzHugh-Nagumo model
Junctions
Neurons
RBF neural networks
Robustness
Sliding mode control
Synchronization
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, an adaptive neural network (NN) sliding mode controller is proposed to realize the chaos synchronization of two gap junction coupled FitzHugh-Nagumo (FHN) neurons under external electrical stimulation. The controller consists of two simple radial basis function (RBF) NNs which are used to approximate the desired sliding mode controller and the uncertain nonlinear part of the error dynamical system, respectively. The weights of these NNs are tuned online based on the sliding mode reaching law. According to the Lyapunov stability theory, the stability of the closed error system is guaranteed. The control scheme is robust to the uncertainties such as approximate error, ionic channel noise and external disturbances. Chaos synchronization are obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.
ISSN:2157-1473
DOI:10.1109/ICMTMA.2011.173