Process / pipelineTranslation-invariant wavelet decomposition
MODWT
标准 DWT 在滤波后进行下采样，因此将输入移位一个样本就会完全改变非零系数的位置——它不是移位不变的。MODWT 通过上采样滤波器而不是下采样数据来保留每个尺度上的所有样本。这会在每个尺度上产生 N 个系数（与输入长度相同），揭示所有振荡，无论其时间相位如何。这就像使用了更精细的时间分辨率来捕捉信号与小波的每一次可能的对齐。
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来源
- Percival, D. B., & Walden, A. T. (1995). Wavelet Methods for Time Series Analysis. Cambridge University Press. link ↗
- Percival, D. B. (2000). Wavelet methods for time series analysis. Cambridge University Press. link ↗
- Whitcher, B., Guttorp, P., & Percival, D. B. (2000). Wavelet analysis of covariance with application to atmospheric time series. Journal of Geophysical Research, 105(D11), 14941–14962. DOI: 10.1029/2000JD900110 ↗
如何引用本页
ScholarGate. (2026, June 3). Maximal Overlap Discrete Wavelet Transform. ScholarGate. https://scholargate.app/zh/time-series/modwt
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