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Synchronization of two identical and non-identical Rulkov models

机译:两个相同和不同的Rulkov模型的同步

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In this paper, the synchronization of two chaotic Rulkov map-based neurons is taken into account. Firstly, based on the master stability function (MSF) analysis, the complete synchronization of two electrical coupled chaotic Rulkov neurons is investigated in detail. The two-dimensional parameter-space plot that displays directly the values of the MSF in different colors is numerically obtained. The numerical values of the MSF show that the two electrical coupled Rulkov neurons are likely to achieve the complete synchronization when each single neuron is in a silent state or a period-1 bursting state, while are unable to reach the complete synchronous state when each single neuron is in a chaotic bursting state or a spiking state. Secondly, Pearson's correlation coefficient is employed to measure the synchronization degree, which demonstrates the nonexistence of the complete synchronization for non-identical electrical coupled Rulkov neurons. Importantly, the complete synchronization can not be reached with the increase of the electrical coupling strength, which is different from the continuous-time neuronal models. Finally, based on the active control method, a synchronization scheme is presented to study the complete synchronization for two Rulkov neurons no matter whether they are identical or not. The scheme is also applied to investigate the anticipated synchronization and the lag synchronization for any two Rulkov neurons. Numerical simulations verify the correctness of our analytical results and the effectiveness of our methods. (C) 2016 Elsevier B.V. All rights reserved.
机译:在本文中,考虑了两个基于混沌Rulkov映射的神经元的同步。首先,基于主稳定性函数(MSF)分析,详细研究了两个电耦合混沌Rulkov神经元的完全同步。以数字方式获得了直接以不同颜色显示MSF值的二维参数空间图。 MSF的数值表明,两个电耦合的Rulkov神经元在每个单个神经元处于静默状态或1期突发状态时都可能实现完全同步,而在每个单个神经元都无法达到完整同步状态时,神经元处于混沌爆发状态或尖峰状态。其次,采用皮尔逊相关系数来衡量同步度,这证明了不相同的电耦合鲁尔科夫神经元完全同步的不存在。重要的是,随着电耦合强度的增加,无法实现完全同步,这与连续时间神经元模型不同。最后,基于主动控制方法,提出了一种同步方案来研究两个Rulkov神经元的完全同步,无论它们是否相同。该方案还用于调查任意两个Rulkov神经元的预期同步和滞后同步。数值模拟验证了我们分析结果的正确性和方法的有效性。 (C)2016 Elsevier B.V.保留所有权利。

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