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  2. Hilbert spectral analysis - Wikipedia

    en.wikipedia.org/wiki/Hilbert_spectral_analysis

    Hilbert spectral analysis is a signal analysis method applying the Hilbert transform to compute the instantaneous frequency of signals according to = (). After performing the Hilbert transform on each signal, we can express the data in the following form:

  3. Spectral theory - Wikipedia

    en.wikipedia.org/wiki/Spectral_theory

    The name spectral theory was introduced by David Hilbert in his original formulation of Hilbert space theory, which was cast in terms of quadratic forms in infinitely many variables. The original spectral theorem was therefore conceived as a version of the theorem on principal axes of an ellipsoid , in an infinite-dimensional setting.

  4. Resolvent formalism - Wikipedia

    en.wikipedia.org/wiki/Resolvent_formalism

    In mathematics, the resolvent formalism is a technique for applying concepts from complex analysis to the study of the spectrum of operators on Banach spaces and more general spaces. Formal justification for the manipulations can be found in the framework of holomorphic functional calculus .

  5. Two-dimensional correlation analysis - Wikipedia

    en.wikipedia.org/wiki/Two-dimensional...

    Two dimensional correlation analysis allows one to determine at which positions in such a measured signal there is a systematic change in a peak, either continuous rising or drop in intensity. 2D correlation analysis results in two complementary signals, which referred to as the 2D synchronous and 2D asynchronous spectrum.

  6. Hilbert–Huang transform - Wikipedia

    en.wikipedia.org/wiki/Hilbert–Huang_transform

    Hilbert spectral analysis (HSA) is a method for examining each IMF's instantaneous frequency as functions of time. The final result is a frequency-time distribution of signal amplitude (or energy), designated as the Hilbert spectrum , which permits the identification of localized features.

  7. Hilbert spectrum - Wikipedia

    en.wikipedia.org/wiki/Hilbert_spectrum

    The Hilbert spectrum (sometimes referred to as the Hilbert amplitude spectrum), named after David Hilbert, is a statistical tool that can help in distinguishing among a mixture of moving signals. The spectrum itself is decomposed into its component sources using independent component analysis .

  8. Multidimensional empirical mode decomposition - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_empirical...

    The Hilbert–Huang empirical mode decomposition (EMD) process decomposes a signal into intrinsic mode functions combined with the Hilbert spectral analysis, known as the Hilbert–Huang transform (HHT). The multidimensional EMD extends the 1-D EMD algorithm into multiple-dimensional signals.

  9. Projection-valued measure - Wikipedia

    en.wikipedia.org/wiki/Projection-valued_measure

    If (X, M) is a standard Borel space, then for every projection-valued measure π on (X, M) taking values in the projections of a separable Hilbert space, there is a Borel measure μ and a μ-measurable family of Hilbert spaces {H x} x ∈ X, such that π is unitarily equivalent to multiplication by 1 E on the Hilbert space