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  2. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Genetics compression algorithms are the latest generation of lossless algorithms that compress data (typically sequences of nucleotides) using both conventional compression algorithms and genetic algorithms adapted to the specific datatype. In 2012, a team of scientists from Johns Hopkins University published a genetic compression algorithm ...

  3. Lempel–Ziv–Storer–Szymanski - Wikipedia

    en.wikipedia.org/wiki/Lempel–Ziv–Storer...

    Lempel–Ziv–Storer–Szymanski (LZSS) is a lossless data compression algorithm, a derivative of LZ77, that was created in 1982 by James A. Storer and Thomas Szymanski. LZSS was described in article "Data compression via textual substitution" published in Journal of the ACM (1982, pp. 928–951). [1] LZSS is a dictionary coding technique. It ...

  4. LZ77 and LZ78 - Wikipedia

    en.wikipedia.org/wiki/LZ77_and_LZ78

    These two algorithms form the basis for many variations including LZW, LZSS, LZMA and others. Besides their academic influence, these algorithms formed the basis of several ubiquitous compression schemes, including GIF and the DEFLATE algorithm used in PNG and ZIP. They are both theoretically dictionary coders. LZ77 maintains a sliding window ...

  5. Tunstall coding - Wikipedia

    en.wikipedia.org/wiki/Tunstall_coding

    Tunstall coding requires the algorithm to know, prior to the parsing operation, what the distribution of probabilities for each letter of the alphabet is. This issue is shared with Huffman coding . Its requiring a fixed-length block output makes it lesser than Lempel–Ziv , which has a similar dictionary-based design, but with a variable-sized ...

  6. Lossless compression - Wikipedia

    en.wikipedia.org/wiki/Lossless_compression

    Algorithms are generally quite specifically tuned to a particular type of file: for example, lossless audio compression programs do not work well on text files, and vice versa. In particular, files of random data cannot be consistently compressed by any conceivable lossless data compression algorithm; indeed, this result is used to define the ...

  7. Lempel–Ziv–Oberhumer - Wikipedia

    en.wikipedia.org/wiki/Lempel–Ziv–Oberhumer

    Allows the user to adjust the balance between compression ratio and compression speed, without affecting the speed of decompression; LZO supports overlapping compression and in-place decompression. As a block compression algorithm, it compresses and decompresses blocks of data. Block size must be the same for compression and decompression.

  8. LZ4 (compression algorithm) - Wikipedia

    en.wikipedia.org/wiki/LZ4_(compression_algorithm)

    The LZ4 algorithm aims to provide a good trade-off between speed and compression ratio. Typically, it has a smaller (i.e., worse) compression ratio than the similar LZO algorithm, which in turn is worse than algorithms like DEFLATE. However, LZ4 compression speed is similar to LZO and several times faster than DEFLATE, while decompression speed ...

  9. Weissman score - Wikipedia

    en.wikipedia.org/wiki/Weissman_score

    The Weissman score is a performance metric for lossless compression applications. It was developed by Tsachy Weissman, a professor at Stanford University, and Vinith Misra, a graduate student, at the request of producers for HBO's television series Silicon Valley, a television show about a fictional tech start-up working on a data compression algorithm.

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