'Prefix code' diaporamas de présentation

COSC 3101A - Design and Analysis of Algorithms 9

COSC 3101A - Design and Analysis of Algorithms 9. Knapsack Problem Huffman Codes Introduction to Graphs. Many of these slides are taken from Monica Nicolescu, Univ. of Nevada, Reno, monica@cs.unr.edu. The Knapsack Problem. The 0-1 knapsack problem

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Huffman Trees and ID3

CS157B Lecture 19. Huffman Trees and ID3. Prof. Sin-Min Lee Department of Computer Science.

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15-853:Algorithms in the Real World

15-853:Algorithms in the Real World. Data Compression: Lectures 1 and 2. Compression in the Real World. Generic File Compression Files : gzip (LZ77), bzip (Burrows-Wheeler), BOA (PPM) Archivers : ARC (LZW), PKZip (LZW+) File systems : NTFS Communication

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T(n) = 4 T(n/3) + ? (n)

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Information Theory Ying Nian Wu UCLA Department of Statistics July 9, 2007 IPAM Summer School

Information Theory Ying Nian Wu UCLA Department of Statistics July 9, 2007 IPAM Summer School. Goal: A gentle introduction to the basic concepts in information theory Emphasis: understanding and interpretations of these concepts

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Greedy Algorithm

Greedy Algorithm. , n ???. Start time?S i. ????? i ,. finish time?f i. or. ???? i , j ???????????????. Activity-selection problem: Problem? ?????????????. Greedy-Activity-Selector(S,f)? Algorithm? Complexity? Thm? ????????????????. , ??? quicksort ?? ~. ??.

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Compression & Huffman Codes

Compression & Huffman Codes. Nelson Padua-Perez William Pugh Department of Computer Science University of Maryland, College Park. Compression. Definition Reduce size of data (number of bits needed to represent data) Benefits Reduce storage needed

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Compression & Huffman Codes

Compression & Huffman Codes. Nelson Padua-Perez Chau-Wen Tseng Department of Computer Science University of Maryland, College Park. Compression. Definition Reduce size of data (number of bits needed to represent data) Benefits Reduce storage needed

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Compression & Huffman Codes

Compression & Huffman Codes. Compression. Definition Reduce size of data (number of bits needed to represent data) Benefits Reduce storage needed Reduce transmission cost / latency / bandwidth. Sources of Compressibility. Redundancy Recognize repeating patterns Exploit using

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4.8 Huffman Codes

4.8 Huffman Codes. These lecture slides are supplied by Mathijs de Weerd. Data Compression. Q. Given a text that uses 32 symbols (26 different letters, space, and some punctuation characters), how can we encode this text in bits ?

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4.8 Huffman Codes

4.8 Huffman Codes. These lecture slides are supplied by Mathijs de Weerd. Data Compression. Q. Given a text that uses 32 symbols (26 different letters, space, and some punctuation characters), how can we encode this text in bits ?

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Chapter 9

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4.8 Huffman Codes

4.8 Huffman Codes. These lecture slides are supplied by Mathijs de Weerd. Data Compression. Q. Given a text that uses 32 symbols (26 different letters, space, and some punctuation characters), how can we encode this text in bits?

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Business Enabled Communications

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Huffman Coding

Huffman Coding. Yancy Vance Paredes. Outline. Background Motivation Huffman Algorithm Sample Implementation Running Time Analysis Proof of Correctness Application. Background. Lossless compression where around 20% to 90% of savings in space Developed by David A. Huffman

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CSC 2300 Data Structures & Algorithms

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Huffman Codes

Analysis of Algorithms. Huffman Codes. Prof. Muhammad Saeed. Standard Coding Scheme. Table Code length=3. Tree. Standard Coding Scheme. Table Code length=3. Tree. Standard Coding Scheme. Table Variable Code Length. Prefix Code. Tree. Standard Coding Scheme. Table.

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MultiMedia Compression

MultiMedia Compression. Images. Audio. Cryptography - Steganography. }. Movies. Codes' type. Statistic code Giving a presentation in a different length to each item according to its probability. Dictionary code A collection of strings.

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Huffman Codes

Huffman Codes. Information coding: Most info transmission machines (computer terminal, Voyager spacecraft) use a binary code. Why? These electric signals are either present or absent at any specific time. Suppose Voyager on-board camera is sensitive to four shades of gray: White Light gray

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Lecture 6. Prefix Complexity K

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