非线性心电对消的Griffith变步长符号FLANN算法

Ke Wang
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引用次数: 0

摘要

心电图是一种微弱的生物电信号,易受噪声的影响,因此噪声的消除在实际应用中起着重要的作用。在此之前,人们提出了各种各样的心电信号去噪算法。然而,上述努力不涉及非线性失真,这可能会遇到的抵消模型。为了解决这一问题,我们提出了一种基于Griffith变步长(VSS)的功能链接人工神经网络符号算法(FLANN-SA)。与现有算法相比,所提算法在信噪比(SNR)和均方误差(MSE)方面均优于现有算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Griffith Variable Step Size Sign FLANN Algorithm for Nonlinear ECG Cancellation
The electrocardiogram (ECG) is a weak bioelectrical signal which is susceptible to noise, hence, the noise cancellation plays an important role for practical applications. Before that, various algorithms have been proposed to ECG denoising. However, the above efforts do not involve the nonlinear distortions, which may encounter in cancellation model. To address this problem, we propose a functional link artificial neural network sign algorithm (FLANN-SA) based on Griffith variable step size (VSS). Compared with existing algorithms, the proposed algorithm exhibits the improved performance than existing algorithms in terms of signal noise ratio (SNR) and the mean square error (MSE).
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