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通信方向依赖耦合下具有未知参数的不同混沌FitzHugh-Nagumo耦合神经元的同步

Synchronization of coupled different chaotic FitzHugh-Nagumo neurons with unknown parameters under communication-direction-dependent coupling.

作者信息

Iqbal Muhammad, Rehan Muhammad, Khaliq Abdul, Hong Keum-Shik

机构信息

Department of Electrical and Computer Engineering, Centre for Advanced Studies in Engineering (CASE), Islamabad 44000, Pakistan.

Department of Electrical Engineering, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 44000, Pakistan.

出版信息

Comput Math Methods Med. 2014;2014:367173. doi: 10.1155/2014/367173. Epub 2014 Jun 30.

Abstract

This paper investigates the chaotic behavior and synchronization of two different coupled chaotic FitzHugh-Nagumo (FHN) neurons with unknown parameters under external electrical stimulation (EES). The coupled FHN neurons of different parameters admit unidirectional and bidirectional gap junctions in the medium between them. Dynamical properties, such as the increase in synchronization error as a consequence of the deviation of neuronal parameters for unlike neurons, the effect of difference in coupling strengths caused by the unidirectional gap junctions, and the impact of large time-delay due to separation of neurons, are studied in exploring the behavior of the coupled system. A novel integral-based nonlinear adaptive control scheme, to cope with the infeasibility of the recovery variable, for synchronization of two coupled delayed chaotic FHN neurons of different and unknown parameters under uncertain EES is derived. Further, to guarantee robust synchronization of different neurons against disturbances, the proposed control methodology is modified to achieve the uniformly ultimately bounded synchronization. The parametric estimation errors can be reduced by selecting suitable control parameters. The effectiveness of the proposed control scheme is illustrated via numerical simulations.

摘要

本文研究了在外部电刺激(EES)下,两个具有未知参数的不同耦合混沌FitzHugh-Nagumo(FHN)神经元的混沌行为和同步。不同参数的耦合FHN神经元在它们之间的介质中允许单向和双向缝隙连接。在探索耦合系统的行为时,研究了诸如由于不同神经元的参数偏差导致同步误差增加、单向缝隙连接引起的耦合强度差异的影响以及神经元分离导致的大时间延迟的影响等动力学特性。推导了一种基于积分的新型非线性自适应控制方案,以应对恢复变量的不可行性,用于在不确定EES下同步两个具有不同和未知参数的耦合延迟混沌FHN神经元。此外,为了保证不同神经元对干扰的鲁棒同步,对所提出的控制方法进行了修改,以实现一致最终有界同步。通过选择合适的控制参数,可以减少参数估计误差。通过数值模拟说明了所提出控制方案的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b6/4101220/66cc76224401/CMMM2014-367173.001.jpg

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