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  2. Discrete wavelet transform - Wikipedia

    en.wikipedia.org/wiki/Discrete_wavelet_transform

    The multiplicative (or geometric) discrete wavelet transform [26] is a variant that applies to an observation model = involving interactions of a positive regular function and a multiplicative independent positive noise, with =.

  3. Coiflet - Wikipedia

    en.wikipedia.org/wiki/Coiflet

    Coiflets are discrete wavelets designed by Ingrid Daubechies, at the request of Ronald Coifman, to have scaling functions with vanishing moments. The wavelet is near symmetric, their wavelet functions have N / 3 {\displaystyle N/3} vanishing moments and scaling functions N / 3 − 1 {\displaystyle N/3-1} , and has been used in many applications ...

  4. Daubechies wavelet - Wikipedia

    en.wikipedia.org/wiki/Daubechies_wavelet

    Daubechies wavelets are widely used in solving a broad range of problems, e.g. self-similarity properties of a signal or fractal problems, signal discontinuities, etc. The Daubechies wavelets are not defined in terms of the resulting scaling and wavelet functions; in fact, they are not possible to write down in closed form.

  5. 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 ...

  6. Cascade algorithm - Wikipedia

    en.wikipedia.org/wiki/Cascade_algorithm

    In the mathematical topic of wavelet theory, the cascade algorithm is a numerical method for calculating function values of the basic scaling and wavelet functions of a discrete wavelet transform using an iterative algorithm. It starts from values on a coarse sequence of sampling points and produces values for successively more densely spaced ...

  7. Wavelet - Wikipedia

    en.wikipedia.org/wiki/Wavelet

    A wavelet is a mathematical function used to divide a given function or continuous-time signal into different scale components. Usually one can assign a frequency range to each scale component. Each scale component can then be studied with a resolution that matches its scale. A wavelet transform is the representation of a function by wavelets.

  8. Lifting scheme - Wikipedia

    en.wikipedia.org/wiki/Lifting_scheme

    The predict step calculates the wavelet function in the wavelet transform. This is a high-pass filter. The update step calculates the scaling function, which results in a smoother version of the data. As mentioned above, the lifting scheme is an alternative technique for performing the DWT using biorthogonal wavelets.

  9. Wavelet transform - Wikipedia

    en.wikipedia.org/wiki/Wavelet_transform

    Discrete wavelet transform has been successfully applied for the compression of electrocardiograph (ECG) signals [6] In this work, the high correlation between the corresponding wavelet coefficients of signals of successive cardiac cycles is utilized employing linear prediction. Wavelet compression is not effective for all kinds of data.