方法证据记录
Empirical Mode Decomposition
Empirical Mode Decomposition (EMD) is a fully data-driven, adaptive method for decomposing nonlinear and non-stationary time series into a finite set of oscillatory components called Intrinsic Mode Functions (IMFs), plus a monotonic residue. Introduced by Norden E. Huang and colleagues at NASA in 1998, EMD requires no predefined basis functions and derives all components directly from the signal itself, making it fundamentally different from Fourier or wavelet transforms.
源记录
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Empirical Mode Decomposition (EMD)
分类方法记录 · ml-model / signal-processing
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