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  2. Multiresolution analysis - Wikipedia

    en.wikipedia.org/wiki/Multiresolution_analysis

    The generating functions are also known as scaling functions or father wavelets. In most cases one demands of those functions to be piecewise continuous with compact support .

  3. 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.

  4. Wavelet transform - Wikipedia

    en.wikipedia.org/wiki/Wavelet_transform

    Scaling of the wavelet-basis-function by this factor and subsequent FFT of this function Multiplication with the transformed signal YFFT of the first step Inverse transformation of the product into the time domain results in Y W ( c , τ ) {\displaystyle Y_{W}(c,\tau )} for different discrete values of τ {\displaystyle \tau } and a discrete ...

  5. Haar wavelet - Wikipedia

    en.wikipedia.org/wiki/Haar_wavelet

    The Haar wavelet. In mathematics, the Haar wavelet is a sequence of rescaled "square-shaped" functions which together form a wavelet family or basis. Wavelet analysis is similar to Fourier analysis in that it allows a target function over an interval to be represented in terms of an orthonormal basis. The Haar sequence is now recognised as the ...

  6. Coiflet - Wikipedia

    en.wikipedia.org/wiki/Coiflet

    Both the scaling function (low-pass filter) and the wavelet function (high-pass filter) must be normalised by a factor /. Below are the coefficients for the scaling functions for C6–30. 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 ...

  7. The wavelets generated by the separable DWT procedure are highly shift variant. A small shift in the input signal changes the wavelet coefficients to a large extent. Also, these wavelets are almost equal in their magnitude in all directions and thus do not reflect the orientation or directivity that could be present in the multidimensional signal.