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  2. Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Huffman_coding

    Huffman tree generated from the exact frequencies of the text "this is an example of a huffman tree". Encoding the sentence with this code requires 135 (or 147) bits, as opposed to 288 (or 180) bits if 36 characters of 8 (or 5) bits were used (This assumes that the code tree structure is known to the decoder and thus does not need to be counted as part of the transmitted information).

  3. Canonical Huffman code - Wikipedia

    en.wikipedia.org/wiki/Canonical_Huffman_code

    The normal Huffman coding algorithm assigns a variable length code to every symbol in the alphabet. More frequently used symbols will be assigned a shorter code. For example, suppose we have the following non-canonical codebook: A = 11 B = 0 C = 101 D = 100

  4. Asymmetric numeral systems - Wikipedia

    en.wikipedia.org/wiki/Asymmetric_numeral_systems

    If symbols are assigned in ranges of lengths being powers of 2, we would get Huffman coding. For example, a->0, b->100, c->101, d->11 prefix code would be obtained for tANS with "aaaabcdd" symbol assignment. Example of generation of tANS tables for m = 3 size alphabet and L = 16 states, then applying them for stream decoding.

  5. Package-merge algorithm - Wikipedia

    en.wikipedia.org/wiki/Package-merge_algorithm

    The optimal length-limited Huffman code will encode symbol i with a bit string of length h i. The canonical Huffman code can easily be constructed by a simple bottom-up greedy method, given that the h i are known, and this can be the basis for fast data compression. [2]

  6. Deflate - Wikipedia

    en.wikipedia.org/wiki/DEFLATE

    The two codes (the 288-symbol length/literal tree and the 32-symbol distance tree) are themselves encoded as canonical Huffman codes by giving the bit length of the code for each symbol. The bit lengths are themselves run-length encoded to produce as compact a representation as possible. As an alternative to including the tree representation ...

  7. Letter frequency - Wikipedia

    en.wikipedia.org/wiki/Letter_frequency

    The California Job Case was a compartmentalized box for printing in the 19th century, sizes corresponding to the commonality of letters. The frequency of letters in text has been studied for use in cryptanalysis, and frequency analysis in particular, dating back to the Arab mathematician al-Kindi (c. AD 801–873 ), who formally developed the method (the ciphers breakable by this technique go ...

  8. AOL Mail

    mail.aol.com/m

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. Modified Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Modified_Huffman_coding

    Modified Huffman coding is used in fax machines to encode black-on-white images . It combines the variable-length codes of Huffman coding with the coding of repetitive data in run-length encoding . The basic Huffman coding provides a way to compress files with much repeating data, like a file containing text, where the alphabet letters are the ...