噪声干扰环境下抑制EMD模态混叠方法

黎恒, 李智, 莫玮, 张绍荣

黎恒, 李智, 莫玮, 张绍荣. 噪声干扰环境下抑制EMD模态混叠方法[J]. 信号处理, 2015, 31(8): 956-961.
引用本文: 黎恒, 李智, 莫玮, 张绍荣. 噪声干扰环境下抑制EMD模态混叠方法[J]. 信号处理, 2015, 31(8): 956-961.
LI Heng, LI Zhi, MO Wei, ZHANG Shao-Rong. Resolving the mode-mixing problem of EMD in the presence of noise[J]. JOURNAL OF SIGNAL PROCESSING, 2015, 31(8): 956-961.
Citation: LI Heng, LI Zhi, MO Wei, ZHANG Shao-Rong. Resolving the mode-mixing problem of EMD in the presence of noise[J]. JOURNAL OF SIGNAL PROCESSING, 2015, 31(8): 956-961.

噪声干扰环境下抑制EMD模态混叠方法

基金项目: 桂林航天工业学院基金项目(YJ1402)
详细信息
  • 中图分类号: TN911.72

Resolving the mode-mixing problem of EMD in the presence of noise

  • 摘要: 经验模态分解(EMD)作为时频分析的经典算法,已经得到广泛的应用。然而,其分解质量容易受到噪声等干扰的影响,产生模态混叠问题。本文针对经验模态分解中因噪声存在的模态混叠问题,提出一种自适应的预处理方法。首先对输入信号进行B样条最小二乘拟合,消除了噪声的影响后,再进行EMD分解。为提高算法的自适应性,提出了一种基于极值点出现时刻的节点选取方法。对线性信号与非线性信号的仿真实验表明该方法有较高的分解精度;与聚合经验模态分解方法(EEMD)的分析对比结果表明该方法能很好地抑制噪声引起的模态混叠。
    Abstract: Empirical mode decomposition has become an established tool for time-frequency analysis and has been widely used. However, a major problem is that its performance of EMD may be affected by intermittence or noise, known as the mode-mixing problem. In order to overcome the mode-mixing problem in the empirical mode decomposition (EMD) algorithm, an adaptive pre-processing technique is proposed. In this work, B-spline least squares approximation is first studied and employed before the use of EMD to eliminate the noise which may result in mode mixing. After that, a knot placement iteration algorithm using the extrema time location is put forward to enhance the adaptive property of the proposed method. Simulations of linear and non-linear signals show that it is capable of significantly reducing mode-mixing problem caused by noise. Comparisons between the proposed method and EEMD method are carried out, indicating that the proposed method is superior to existing methods in accuracy.
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出版历程
  • 收稿日期:  2015-01-08
  • 修回日期:  2015-05-05
  • 发布日期:  2015-08-24

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