000 | 04795nam a22004935i 4500 | ||
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001 | 978-1-84628-959-0 | ||
003 | DE-He213 | ||
005 | 20201213200635.0 | ||
007 | cr nn 008mamaa | ||
008 | 100602s2007 xxk| s |||| 0|eng d | ||
020 |
_a9781846289590 _9978-1-84628-959-0 |
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024 | 7 |
_a10.1007/978-1-84628-959-0 _2doi |
|
050 | 4 | _aQA268 | |
072 | 7 |
_aGPJ _2bicssc |
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072 | 7 |
_aGPF _2bicssc |
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072 | 7 |
_aCOM031000 _2bisacsh |
|
082 | 0 | 4 |
_a003.54 _223 |
100 | 1 |
_aSalomon, David. _eauthor. |
|
245 | 1 | 0 |
_aVariable-length Codes for Data Compression _h[electronic resource] / _cby David Salomon. |
264 | 1 |
_aLondon : _bSpringer London, _c2007. |
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300 | _bonline resource. | ||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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505 | 0 | _aFrom the contents -- Codes, Fixed- and Variable-Length -- Prefix Codes -- VLCs, Entropy, and Redundancy -- Universal Codes -- The Kraft-MacMillan Inequality -- Tunstall Code -- Schalkwijk’s Coding -- Tjalkens-Willems V-to-B Coding -- Phased-In Codes -- Redundancy Feedback (RF) Coding -- Recursive Phased-In codes -- Self-Delimiting Codes -- Huffman Coding -- VLCs for Integers -- Start-Step-Stop Codes -- Start/Stop Codes -- Elias Codes -- Levenstein Code -- Even Rodeh Code -- Punctured Elias Codes -- Other Prefix Codes -- Ternary Comma Code -- Location Based Encoding (LBE) -- Stout Codes -- Yamamoto’s Recursive Code -- VLCs and Search Trees -- Taboo Codes -- Wang’s Flag Code -- Yamamoto Flag Code -- Number Bases -- Fibonacci Code -- Generalized Fibonacci Codes -- Goldbach Codes -- Additive Codes -- Golomb Code -- Rice Codes -- Subexponential Code -- Codes Ending with '1' -- Codes for Error Control -- The Free Distance -- Synchronous Prefix Codes -- Resynchronizing Huffman Codes -- Bidirectional Codes -- Symmetric Codes -- VLEC Codes -- Summary. | |
520 | _aMost data compression methods that are based on variable-length codes employ the Huffman or Golomb codes. However, there are a large number of less-known codes that have useful properties - such as those containing certain bit patterns, or those that are robust - and these can be useful. This book brings this large set of codes to the attention of workers in the field and to students of computer science. David Salomon’s clear style of writing and presentation, which has been familiar to readers for many years now, allows easy access to this topic. This comprehensive text offers readers a detailed, reader-friendly description of the variable length codes used in the field of data compression. Readers are only required to have a general familiarity with computer methods and essentially an understanding of the representation of data in bits and files. Topics and Features: • Discusses codes in-depth, not the compression algorithms, which are readily available in many books • Includes detailed illustrations, providing readers with a deeper and broader understanding of the topic • Provides a supplementary author-maintained website, with errata and auxiliary material – www.davidsalomon.name/VLCadvertis/VLC.html • Easily understood and used by computer science majors requiring only a minimum of mathematics • Can easily be used as a main or auxiliary textbook for courses on algebraic codes or data compression and protection • An ideal companion volume to David Salomon’s fourth edition of Data Compression: The Complete Reference Computer scientists, electrical engineers and students majoring in computer science or electrical engineering will find this volume a valuable resource, as will those readers in various physical sciences and mathematics. David Salomon is a professor emeritus of Computer Science at California State University, Northridge. He has authored numerous articles and books, including Coding for Data and Computer Communications, Guide to Data Compression Methods, Data Privacy and Security, Computer Graphics and Geometric Modeling, Foundations of Computer Security, and Transformations and Projections in Computer Graphics. | ||
650 | 0 | _aComputer science. | |
650 | 0 | _aData encryption (Computer science). | |
650 | 0 | _aCoding theory. | |
650 | 0 | _aComputer vision. | |
650 | 1 | 4 | _aComputer Science. |
650 | 2 | 4 | _aCoding and Information Theory. |
650 | 2 | 4 | _aData Storage Representation. |
650 | 2 | 4 | _aData Encryption. |
650 | 2 | 4 | _aImage Processing and Computer Vision. |
650 | 2 | 4 | _aSignal, Image and Speech Processing. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9781846289583 |
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-84628-959-0 |
912 | _aZDB-2-SCS | ||
950 | _aComputer Science (Springer-11645) | ||
999 |
_c13180 _d13180 |