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・ Hilbert's theorem (differential geometry)
・ Hilbert's Theorem 90
・ Hilbert's third problem
・ Hilbert's thirteenth problem
・ Hilbert's twelfth problem
・ Hilbert's twentieth problem
・ Hilbert's twenty-first problem
・ Hilbert's twenty-fourth problem
・ Hilbert's twenty-second problem
・ Hilbert's twenty-third problem
・ Hilbert, West Virginia
・ Hilbert, Wisconsin
・ Hilbert–Bernays paradox
・ Hilbert–Bernays provability conditions
・ Hilbert–Burch theorem
Hilbert–Huang transform
・ Hilbert–Kunz function
・ Hilbert–Mumford criterion
・ Hilbert–Poincaré series
・ Hilbert–Pólya conjecture
・ Hilbert–Samuel function
・ Hilbert–Schmidt
・ Hilbert–Schmidt integral operator
・ Hilbert–Schmidt operator
・ Hilbert–Schmidt theorem
・ Hilbert–Smith conjecture
・ Hilbert–Speiser theorem
・ Hilbesheim
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Hilbert–Huang transform : ウィキペディア英語版
Hilbert–Huang transform

The Hilbert–Huang transform (HHT) is a way to decompose a signal into so-called intrinsic mode functions (IMF) along with a trend, and obtain instantaneous frequency data. It is designed to work well for data that is nonstationary and nonlinear. In contrast to other common transforms like the Fourier transform, the HHT is more like an algorithm (an empirical approach) that can be applied to a data set, rather than a theoretical tool.
== Introduction ==
The Hilbert–Huang transform (HHT), a NASA designated name, was proposed by Huang et al. (1996, 1998, 1999, 2003, 2012). It is the result of the empirical mode decomposition (EMD) and the Hilbert spectral analysis (HSA). The HHT uses the EMD method to decompose a signal into so-called intrinsic mode functions (IMF) with a trend, and applies the HSA method to the IMFs to obtain instantaneous frequency data. Since the signal is decomposed in time domain and the length of the IMFs is the same as the original signal, HHT preserves the characteristics of the varying frequency. This is an important advantage of HHT since real-world signal usually has multiple causes happening in different time intervals. The HHT provides a new method of analyzing nonstationary and nonlinear time series data.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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