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这里介绍了如何利用LabVIEW进行信号预处理，对进行信号分析很有价值-here on how to use LabVIEW signal preprocessing, the signal valuable analysis
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将高阶时频表示引入机械故障诊断领域。介绍了Wigner 高阶矩谱(WHOS)的概念、定义。针对多分量信号Wigner 高阶矩谱的交叉项会产生“虚假信号”,结合局域波法, 提出了一种抑制WHOS交叉项的新方法。首先对复杂信号进行预处理, 利用局域波分解方法把其分解成有限个具有单分量特性的基本模式分量,然后对每个基本模式分量计算WHOS。该方法能有效抑制WHOS时频分布的交叉项。通过仿真实验和转子的故障实验,以Wigner 双谱为例, 验证了该方法的实用性,为故障诊断的特征提取提供了新的工具-Hig
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从高噪下提取微弱信号是工程中在信号预处理中很重要的一个分支。故该课题要求同学在分析弱信号的特点基础上，研究不同算法在弱信号检测上的优缺点-Extract weak signals from noisy signal preprocessing engineering in a very important branch. Therefore, the subject requires students to analyze the characteristics of a weak signal
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ue to the volume conduction multichannel electroencephalogram (EEG) recordings
give a rather blurred image of brain activity. Therefore spatial filters are
extremely useful in single-trial analysis in order to improve the signal-to-noise
ratio.
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The Bland–Altman analysis for repeated measures on 10-minute
time windows in the awake state (around 7 PM) and during sleep
(around 12 AM) was used to compare OHR and HRECG [6]. The
Mann–Whitney U-test was used to compare the average HRECG and
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This paper gives an insight to labview software tools which helps in analysis of ECG signals. The raw ECG data are taken MIT-BIH Arrhythmia . Study of ECG signal includes filtering & preprocessing which removes the baseline wandering and noise due to
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主要用于信号的预处理去噪，经过变换以后实现信号的重构，具有很好的效果。(It is mainly used for signal preprocessing de-noising, after transformation, it can realize the reconstruction of the signal, which has good effect.)
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