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A Synchronization Criterion for Two Hindmarsh-Rose Neurons with Linear and Nonlinear Coupling Functions Based on the Laplace Transform Method
Author(s) -
Chun-Lin Su,
Bin Zhen,
Zigen Song
Publication year - 2021
Publication title -
neural plasticity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.288
H-Index - 68
eISSN - 2090-5904
pISSN - 1687-5443
DOI - 10.1155/2021/6692132
Subject(s) - laplace transform , synchronization (alternating current) , nonlinear system , coupling (piping) , control theory (sociology) , mathematics , lyapunov stability , stability criterion , chaotic , computer science , topology (electrical circuits) , mathematical analysis , artificial intelligence , physics , engineering , mechanical engineering , statistics , control (management) , discrete time and continuous time , quantum mechanics , combinatorics
In this paper, an analytical criterion is proposed to investigate the synchronization between two Hindmarsh-Rose neurons with linear and nonlinear coupling functions based on the Laplace transform method. Different from previous works, the synchronization error system is expressed in its integral form, which is more convenient to analyze. The synchronization problem of two HR coupled neurons is ultimately converted into the stability problem of roots to a nonlinear algebraic equation. Then, an analytical criterion for synchronization between the two HR neurons can be given by using the Routh-Hurwitz criterion. Numerical simulations show that the synchronization criterion derived in this paper is valid, regardless of the periodic spikes or burst-spike chaotic behavior of the two HR neurons. Furthermore, the analytical results have almost the same accuracy as the conditional Lyapunov method. In addition, the calculation quantities always are small no matter the linear and nonlinear coupling functions, which show that the approach presented in this paper is easy to be developed to study synchronization between a large number of HR neurons.

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