基于鲁棒不动点变换的耦合神经元自适应同步简单降噪

T. A. Várkonyi, J. Tar, J. Bitó, I. Rudas
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引用次数: 5

摘要

为了避免Lyapunov“直接”方法在自适应控制中应用的一般数学困难,本文提出了一种替代方法,即使用“鲁棒不动点变换(RFPT)”用于两个耦合的,不对称的,混沌行为的,近似已知的Fitz - Hugh - Nagumo (FHN)神经元的自适应同步。由于RFPT方案是基于“预期-实现响应方案”的使用,因此观测量中的噪声可能会影响控制器的效率。为此,提出了一种非常简单,易于实现的技术,即在时域中应用多项式滤波系数。通过扩展的仿真研究验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simple noise reduction in the adaptive synchronization of coupled neurons by Robust Fixed Point Transformation
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.
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