东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2009, Vol. 30 ›› Issue (3): 333-336.DOI: -

• 论著 • 上一篇    下一篇

基于改进阈值函数的体震信号平移不变去噪

金晶晶;王旭;吴雪;杨丹;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2009-03-15 发布日期:2013-06-22
  • 通讯作者: Jin, J.-J.
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(50477015)

Translation-invariant de-noising of body fluttering signal based on improved threshold function

Jin, Jing-Jing (1); Wang, Xu (1); Wu, Xue (1); Yang, Dan (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2009-03-15 Published:2013-06-22
  • Contact: Jin, J.-J.
  • About author:-
  • Supported by:
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摘要： 体震信号微弱,受仪器、环境因素等方面的影响,常常含有大量噪声,研究一种基于改进阈值函数的平移不变法用于体震信号的去噪.针对体震信号选择了合适的小波基,说明了小波分解后各尺度上噪声方差的估计方法,分析了所改进阈值函数的性能及特点,并给出了算法的实现步骤.与基于硬、软阈值函数平移不变法的去噪效果比较,基于改进阈值函数平移不变法去噪后的体震信号波形平滑,特征点幅值无衰减.其功率谱密度与原始信号功率谱密度的对比结果表明,基于改进阈值函数的平移不变法能够在去噪的同时更好地保留原始体震信号的特征.

关键词: 体震信号, 平移不变去噪, 噪声方差, 改进阈值函数, 功率谱密度

Abstract: Body fluttering signal is weak and often involves a lot of noise arising from instrument and environment. The translation-invariant de-noising method based on improved threshold function was therefore studied to de-noise the body fluttering signal. A proper wavelet base suitable to body fluttering was selected, and the estimate method of noise variance on each and every scale after wavelet decomposition was analyzed. In addition, the capability and characteristics of improved threshold function were analyzed, based on which the translation-invariant de-noising method was applied to de-noising body fluttering signal with relevant algorithm given to implement the de-noising process. Compared the de-noised results by both hard and soft threshold functions, the body fluttering signal presents smooth wave shape with no attenuated amplitude at characteristic points. The comparison results of power spectral density between translation-invariant de-noised signal and original body fluttering signal revealed that the former can keep the characteristics of original body fluttering signal when de-noising.

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