Adaptive synchronization for nonlinear FitzHugh-Nagumo neurons in external electrical stimulation

Chung Wen Lai; Chang Kuo Chen; Teh Lu Liao; Jun Juh Yan

doi:10.1002/acs.1022

Adaptive synchronization for nonlinear FitzHugh-Nagumo neurons in external electrical stimulation

Chung Wen Lai, Chang Kuo Chen, Teh Lu Liao, Jun Juh Yan

Department of Engineering Science

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

This paper investigates the synchronization problem for FitzHugh-Nagumo (FHN) neurons in external electrical stimulations. Using the sliding mode control technique, an adaptive control law is established that guarantees synchronization even when the parameters of the master and slave FHN neurons are fully unknown. A proportional-integral switching surface is introduced to simplify the task of assigning the stability of the closed-loop error system in the sliding mode. Furthermore, the proposed synchronization scheme is then applied to a secure communication system. Computer simulations are provided to verify the effectiveness of the proposed adaptive synchronization scheme.

Original language	English
Pages (from-to)	833-844
Number of pages	12
Journal	International Journal of Adaptive Control and Signal Processing
Volume	22
Issue number	9
DOIs	https://doi.org/10.1002/acs.1022
Publication status	Published - 2008 Nov

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Signal Processing
Electrical and Electronic Engineering

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10.1002/acs.1022

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abstract = "This paper investigates the synchronization problem for FitzHugh-Nagumo (FHN) neurons in external electrical stimulations. Using the sliding mode control technique, an adaptive control law is established that guarantees synchronization even when the parameters of the master and slave FHN neurons are fully unknown. A proportional-integral switching surface is introduced to simplify the task of assigning the stability of the closed-loop error system in the sliding mode. Furthermore, the proposed synchronization scheme is then applied to a secure communication system. Computer simulations are provided to verify the effectiveness of the proposed adaptive synchronization scheme.",

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AB - This paper investigates the synchronization problem for FitzHugh-Nagumo (FHN) neurons in external electrical stimulations. Using the sliding mode control technique, an adaptive control law is established that guarantees synchronization even when the parameters of the master and slave FHN neurons are fully unknown. A proportional-integral switching surface is introduced to simplify the task of assigning the stability of the closed-loop error system in the sliding mode. Furthermore, the proposed synchronization scheme is then applied to a secure communication system. Computer simulations are provided to verify the effectiveness of the proposed adaptive synchronization scheme.

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Adaptive synchronization for nonlinear FitzHugh-Nagumo neurons in external electrical stimulation

Abstract

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