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Simple noise reduction in the adaptive synchronization of coupled neurons by Robust Fixed Point Transformation

机译:耦合神经元的自适应同步稳健固定点变换简单降噪

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To avoid the general mathematical difficulties of the application of Lyapunov's “direct” method in adaptive control in the present paper an alternative approach, the use of “Robust Fixed Point Transformation (RFPT)” is applied for the adaptive synchronization of two coupled, asymmetric, chaotically behaving, approximately known Fitz — Hugh — Nagumo (FHN) neurons. Since the RFPT scheme is based on the use of the “Expected — Realized Response Scheme” the noise in the observed quantities may influence the efficiency of the controller. For this purpose the use of a very simple, easily realizable technique is proposed that applies polynomial filtering coefficients in the time domain. Its efficiency is investigated and substantiated via extended simulation investigations.
机译:为了避免Lyapunov的应用程序的一般数学困难。直接” 自适应控制中的方法在本文中的一种替代方法,使用“鲁棒的固定点变换(RFPT)” 应用于两个耦合,不对称,络合行为的自适应同步,大约已知的Fitz - Hugh - Nagumo(FHN)神经元。 由于RFPT方案基于使用“预期的 - 实现响应计划” 观察量中的噪声可以影响控制器的效率。 为此目的,提出了使用非常简单的易于可实现的技术,其在时域中应用多项式滤波系数。 通过扩展模拟调查调查和证实其效率。

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