When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Shannon–Fano coding - Wikipedia

    en.wikipedia.org/wiki/Shannon–Fano_coding

    For another, both Shannon’s and Fano’s coding schemes are similar in the sense that they both are efficient, but suboptimal prefix-free coding schemes with a similar performance. Shannon's (1948) method, using predefined word lengths, is called Shannon–Fano coding by Cover and Thomas, [ 4 ] Goldie and Pinch, [ 5 ] Jones and Jones, [ 6 ...

  3. Shannon coding - Wikipedia

    en.wikipedia.org/wiki/Shannon_coding

    In the field of data compression, Shannon coding, named after its creator, Claude Shannon, is a lossless data compression technique for constructing a prefix code based on a set of symbols and their probabilities (estimated or measured).

  4. Prefix code - Wikipedia

    en.wikipedia.org/wiki/Prefix_code

    As with a prefix code, the representation of a string as a concatenation of such words is unique. A bifix code is a set of words which is both a prefix and a suffix code. [8] An optimal prefix code is a prefix code with minimal average length. That is, assume an alphabet of n symbols with probabilities () for a prefix code C.

  5. Shannon–Fano–Elias coding - Wikipedia

    en.wikipedia.org/wiki/Shannon–Fano–Elias_coding

    Shannon–Fano–Elias coding produces a binary prefix code, allowing for direct decoding. Let bcode(x) be the rational number formed by adding a decimal point before a binary code. For example, if code(C) = 1010 then bcode(C) = 0.1010. For all x, if no y exists such that

  6. Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Huffman_coding

    In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression.The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Huffman while he was a Sc.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes".

  7. Trie - Wikipedia

    en.wikipedia.org/wiki/Trie

    In computer science, a trie (/ ˈ t r aɪ /, / ˈ t r iː /), also known as a digital tree or prefix tree, [1] is a specialized search tree data structure used to store and retrieve strings from a dictionary or set.

  8. Kraft–McMillan inequality - Wikipedia

    en.wikipedia.org/wiki/Kraft–McMillan_inequality

    Let each source symbol from the alphabet = {,, …,} be encoded into a uniquely decodable code over an alphabet of size with codeword lengths ,, …,. Then = Conversely, for a given set of natural numbers ,, …, satisfying the above inequality, there exists a uniquely decodable code over an alphabet of size with those codeword lengths.

  9. Self-synchronizing code - Wikipedia

    en.wikipedia.org/wiki/Self-synchronizing_code

    The prefix code {00, 11} is not self-synchronizing; while 0, 1, 01 and 10 are not codes, 00 and 11 are. The prefix code {ab,ba} is not self-synchronizing because abab contains ba. The prefix code b ∗ a (using the Kleene star) is not self-synchronizing (even though any new code word simply starts after a) because code word ba contains code word a.