Empirical mode decomposition
Multiplying your exposure to uncertainty principles
2018-01-05 — 2022-07-12
Wherein a signal is rendered into intrinsic mode functions by an iterative sifting process, and instantaneous frequency content is obtained via the Hilbert transform for analysis of nonlinear, non‑stationary records.
functional analysis
Hilbert space
probability
signal processing
Placeholder for a non-stationary, non-linear signal decomposition method unlike the windowed stationary techniques of yore.
- Hilbert-Huang Transform and Its Applications
- The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
- Why use EMD?
- Hilbert–Huang transform
1 References
Huang, Norden E, and Shen. 2005a. Hilbert-Huang Transform and Its Applications. Interdisciplinary Mathematical Sciences.
———. 2005b. “Introduction to the Hilbert Huang Transform and Its Related Mathematical Problems.” In Hilbert-Huang Transform and Its Applications. Interdisciplinary Mathematical Sciences.
Huang, Norden E., Shen, Long, et al. 1998. “The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis.” Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.