Inertial Sensors Random Sequence Pretreatment Using Empirical Mode Decomposition Method

2011 International Conference on Multimedia and Signal Processing Pub Date : 2011-05-14 DOI:10.1109/CMSP.2011.139

Zhang Qiu-zhao, Zhang Shu-bi, Hou Dong-yang

引用次数: 0

Abstract

A new signal analysis technique -- empirical mode decomposition (EMD) method is introduced for removing the trend term of nonstationary random sequence. An inverse sequence method is used to check the effect of EMD method. The experiment indicates that the EMD method can not only eliminate the trend term of nonstationary random sequence, but also improve the normal natures of the nonstationary random sequence.

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惯性传感器随机序列的经验模态分解预处理

介绍了一种新的信号分析技术——经验模态分解(EMD)方法，用于去除非平稳随机序列的趋势项。用逆序列法检验了EMD方法的效果。实验表明，EMD方法不仅可以消除非平稳随机序列的趋势项，而且可以改善非平稳随机序列的正态性。

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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来源期刊

2011 International Conference on Multimedia and Signal Processing

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