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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

    In computer science and information theory, a canonical Huffman code is a particular type of Huffman code with unique properties which allow it to be described in a very compact manner. Rather than storing the structure of the code tree explicitly, canonical Huffman codes are ordered in such a way that it suffices to only store the lengths of ...

  4. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    A greedy algorithm is used to construct a Huffman tree during Huffman coding where it finds an optimal solution. In decision tree learning, greedy algorithms are commonly used, however they are not guaranteed to find the optimal solution. One popular such algorithm is the ID3 algorithm for decision tree construction.

  5. Puzzle solutions for Saturday, Nov. 30, 2024

    www.aol.com/news/puzzle-solutions-saturday-nov...

    Find answers to the latest online sudoku and crossword puzzles that were published in USA TODAY Network's local newspapers.

  6. Adaptive Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Adaptive_Huffman_coding

    Adaptive Huffman coding (also called Dynamic Huffman coding) is an adaptive coding technique based on Huffman coding. It permits building the code as the symbols are being transmitted, having no initial knowledge of source distribution, that allows one-pass encoding and adaptation to changing conditions in data.

  7. Van Emde Boas tree - Wikipedia

    en.wikipedia.org/wiki/Van_Emde_Boas_tree

    If T.min = T.max = x then x is the only element stored in the tree and we set T.min = M and T.max = −1 to indicate that the tree is empty. Otherwise, if x == T.min then we need to find the second-smallest value y in the vEB tree, delete it from its current location, and set T.min=y.

  8. Orange Cat Gets His Own Christmas Tree and He ‘Absolutely ...

    www.aol.com/orange-cat-gets-own-christmas...

    People loved the orange cat's reaction to the tree and had a lot to say about Abram's video. @Jen got more than 300 likes when she pointed out, "He's the angel on top of his tree!"

  9. Business owners should not forget anti-money laundering rule ...

    www.aol.com/news/business-owners-not-forget-anti...

    Small business owners should not forget about a rule — currently in legal limbo — that would require them to register with an agency called the Financial Crimes Enforcement Network, or FinCEN ...