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  2. Stretched exponential function - Wikipedia

    en.wikipedia.org/wiki/Stretched_exponential_function

    With β = 1, the usual exponential function is recovered. With a stretching exponent β between 0 and 1, the graph of log f versus t is characteristically stretched, hence the name of the function. The compressed exponential function (with β > 1) has less practical importance, with the notable exception of β = 2, which gives the normal ...

  3. Zopfli - Wikipedia

    en.wikipedia.org/wiki/Zopfli

    By default, Zopfli performs 15 iterations but could be configured to perform more or fewer. Under default settings, the output of Zopfli is typically 3–8% smaller than zlib's maximum compression, but takes around 80 times longer. [4] [3] Because of its significantly slower compression speed, Zopfli is not suited for on-the-fly compression.

  4. Graph Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Graph_Fourier_transform

    In mathematics, the graph Fourier transform is a mathematical transform which eigendecomposes the Laplacian matrix of a graph into eigenvalues and eigenvectors.Analogously to the classical Fourier transform, the eigenvalues represent frequencies and eigenvectors form what is known as a graph Fourier basis.

  5. Iterative compression - Wikipedia

    en.wikipedia.org/wiki/Iterative_compression

    Test whether the (k + 1)-vertex solution Y = X ∪ {v} to S can be compressed to a k-vertex solution. If it cannot be compressed, abort the algorithm: the input graph has no k-vertex solution. Otherwise, set X to the new compressed solution and continue the loop. This algorithm calls the compression subroutine a linear number of times.

  6. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/Lossless_compression

    Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy . [ 1 ]

  7. Prediction by partial matching - Wikipedia

    en.wikipedia.org/wiki/Prediction_by_partial_matching

    In many compression algorithms, the ranking is equivalent to probability mass function estimation. Given the previous letters (or given a context), each symbol is assigned with a probability. For instance, in arithmetic coding the symbols are ranked by their probabilities to appear after previous symbols, and the whole sequence is compressed ...

  8. Golomb coding - Wikipedia

    en.wikipedia.org/wiki/Golomb_coding

    Golomb coding is a lossless data compression method using a family of data compression codes invented by Solomon W. Golomb in the 1960s. Alphabets following a geometric distribution will have a Golomb code as an optimal prefix code, [1] making Golomb coding highly suitable for situations in which the occurrence of small values in the input stream is significantly more likely than large values.

  9. Fractal compression - Wikipedia

    en.wikipedia.org/wiki/Fractal_compression

    2 triangles, example to show how fractal compression works. Fractal compression is a lossy compression method for digital images, based on fractals.The method is best suited for textures and natural images, relying on the fact that parts of an image often resemble other parts of the same image. [1]