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  2. Wavelet - Wikipedia

    en.wikipedia.org/wiki/Wavelet

    This means that there has to exist an auxiliary function, the father wavelet φ in L 2 (R), and that a is an integer. A typical choice is a = 2 and b = 1. The most famous pair of father and mother wavelets is the Daubechies 4-tap wavelet. Note that not every orthonormal discrete wavelet basis can be associated to a multiresolution analysis; for ...

  3. Cohen–Daubechies–Feauveau wavelet - Wikipedia

    en.wikipedia.org/wiki/Cohen–Daubechies...

    An example of the 2D wavelet transform that is used in JPEG 2000. Cohen–Daubechies–Feauveau wavelets are a family of biorthogonal wavelets that was made popular by Ingrid Daubechies. [1] [2] These are not the same as the orthogonal Daubechies wavelets, and also not very similar in shape and properties. However, their construction idea is ...

  4. Daubechies wavelet - Wikipedia

    en.wikipedia.org/wiki/Daubechies_wavelet

    Daubechies orthogonal wavelets D2–D20 resp. db1–db10 are commonly used. Each wavelet has a number of zero moments or vanishing moments equal to half the number of coefficients. For example, D2 has one vanishing moment, D4 has two, etc. A vanishing moment limits the wavelets ability to represent polynomial behaviour or information in a ...

  5. Chirplet transform - Wikipedia

    en.wikipedia.org/wiki/Chirplet_transform

    Comparison of wave, wavelet, chirp, and chirplet [1] Chirplet in a computer-mediated reality environment.. In signal processing, the chirplet transform is an inner product of an input signal with a family of analysis primitives called chirplets.

  6. Morlet wavelet - Wikipedia

    en.wikipedia.org/wiki/Morlet_wavelet

    The Morlet wavelet transform is capable of capturing short bursts of repeating and alternating music notes with a clear start and end time for each note. [citation needed] A modified morlet wavelet was proposed to extract melody from polyphonic music. [11] This methodology is designed for the detection of closed frequency.

  7. Coiflet - Wikipedia

    en.wikipedia.org/wiki/Coiflet

    The wavelet coefficients are derived by reversing the order of the scaling function coefficients and then reversing the sign of every second one (i.e. C6 wavelet = {−0.022140543057, 0.102859456942, 0.544281086116, −1.205718913884, 0.477859456942, 0.102859456942}).

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