Using a variation of empirical mode decomposition to remove noise from signals

M. Kaleem, A. Guergachi, S. Krishnan, A. Çetin
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引用次数: 6

Abstract

This paper will describe the application of τ-based decomposition, which is a variation of the empirical mode decomposition method based on modified peak selection, to de-noising and de-trending of signals. The τ-based decomposition method will be explained, and its application to synthetic and real-world signals in the context of de-noising and de-trending will be described. Comparison between the computational simplicity of the τ-based decomposition method to de-noising and de-trending of signals and approaches based on empirical mode decomposition will be highlighted.
利用经验模态分解的变化来去除信号中的噪声
本文将描述基于τ的分解(一种基于修正峰选择的经验模态分解方法)在信号去噪和去趋势中的应用。将解释基于τ的分解方法,并描述其在去噪和去趋势背景下对合成信号和实际信号的应用。将重点比较基于τ的分解方法对信号去噪和去趋势的计算简洁性和基于经验模态分解的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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