文件名称:xujiayshangchuan
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经验模态分解(Empirical Mode Decomposition,简称EMD)法是美籍华人N. E. Huang等人于1998年提出的,适合于分析非线性、非平稳信号序列,具有很高的信噪比。该方法的关键是经验模式分解,它能使复杂信号分解为有限个本征模函数(Intrinsic Mode Function,简称IMF),所分解出来的各IMF分量包含了原信号的不同时间尺度的局部特征信号。-Empirical Mode Decomposition method (Empirical Mode Decomposition, the EMD for short) is a chinese-american n. e. Huang et al., in 1998, is suitable for analyzing nonlinear and non-stationary signal sequence, has the very high signal-to-noise ratio.Empirical Mode decomposition is a key to this method, it can make the complex signal is decomposed into a finite number of Intrinsic Mode Function (the Intrinsic Mode Function, the IMF), the decomposition of each IMF component contains the original signals of the local characteristics of different time scales.
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下载文件列表
xujiayshangchuan/BPnet2222work.m
xujiayshangchuan/emd125.m
xujiayshangchuan/yangben.m
xujiayshangchuan/希尔伯特-黄变换说明及程序.docx
xujiayshangchuan/
xujiayshangchuan/emd125.m
xujiayshangchuan/yangben.m
xujiayshangchuan/希尔伯特-黄变换说明及程序.docx
xujiayshangchuan/
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