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中值互补集合经验模态分解
刘淞华; 何冰冰; 郎恂; 陈启明; 张榆锋; 苏宏业
Source Publication自动化学报
ISSN0254-4156
2023
Volume49Issue:12Pages:2544-2556
Abstract针对经验模态分解(Empirical mode decomposition, EMD)系列方法存在的模态分裂(Mode splitting, MS)问题,提出中值互补集合经验模态分解(Median complementary ensemble EMD, MCEEMD)算法.通过概率模型量化互补集合经验模态分解(Complementary ensemble EMD, CEEMD)的MS问题,证明了使用中值算子替代算术平均算子对抑制MS的有效性.为了兼具抑制MS和残留噪声的性能, MCEEMD算法首次在集合过程中结合了中值和平均算子.具体地,所提方法首先添加N对互补的白噪声至原信号中,并经过EMD分解得到2N组固有模态函数(Intrinsic mode functions, IMFs),然后分别对其中互补相关的IMFs两两取平均得到N组IMFs,最后使用中值算子处理上述N组IMFs得到输出结果.对仿真信号与两个真实案例的分析结果表明,本文提出的MCEEMD方法不仅有效抑制了CEEMD的MS问题,而且避免了单一使用中值算子的两个缺点:分解完备性差和IMFs中存在的毛刺现象.
Keyword模态分裂 中值算子 互补白噪声 互补集合经验模式分解
DOI10.16383/j.aas.c201031
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/55773
Collection学术期刊_自动化学报
Recommended Citation
GB/T 7714
刘淞华,何冰冰,郎恂,等. 中值互补集合经验模态分解[J]. 自动化学报,2023,49(12):2544-2556.
APA 刘淞华,何冰冰,郎恂,陈启明,张榆锋,&苏宏业.(2023).中值互补集合经验模态分解.自动化学报,49(12),2544-2556.
MLA 刘淞华,et al."中值互补集合经验模态分解".自动化学报 49.12(2023):2544-2556.
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