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The compressed exponential function (with β > 1) has less practical importance, with the notable exceptions of β = 2, which gives the normal distribution, and of compressed exponential relaxation in the dynamics of amorphous solids. [1] In mathematics, the stretched exponential is also known as the complementary cumulative Weibull distribution.
Power graph analysis is the computation, analysis and visual representation of a power graph from a graph . Power graph analysis can be thought of as a lossless compression algorithm for graphs. [1] It extends graph syntax with representations of cliques, bicliques and stars.
Zopfli is a data compression library that performs Deflate, gzip and zlib data encoding. [2] It achieves higher compression ratios than mainstream Deflate and zlib implementations at the cost of being slower. [3] Google first released Zopfli in February 2013 under the terms of Apache License 2.0. [4]
In computer science, iterative compression is an algorithmic technique for the design of fixed-parameter tractable algorithms, in which one element (such as a vertex of a graph) is added to the problem in each step, and a small solution for the problem prior to the addition is used to help find a small solution to the problem after the step.
for each pixel (Px, Py) on the screen do x0:= scaled x coordinate of pixel (scaled to lie in the Mandelbrot X scale (-2.5, 1)) y0:= scaled y coordinate of pixel (scaled to lie in the Mandelbrot Y scale (-1, 1)) x:= 0.0 y:= 0.0 iteration:= 0 max_iteration:= 1000 // Here N = 2^8 is chosen as a reasonable bailout radius. while x*x + y*y ≤ (1 ...
Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:
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 ...
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 ]