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journal = jBELLSYSTTECHJ,
volume = "30",
number = "1",
pages = "5064",
month = jan,
year = "1951",
CODEN = "BSTJAN",
ISSN = "00058580",
ISSNL = "",
bibdate = "Sat Jan 26 12:46:16 MST 2013",
bibsource = "http://bstj.belllabs.com/oldfiles/year.1951/BSTJ.1951.3001.html;
http://www.alcatellucent.com/bstj/vol301951/bstjvol30issue01.html;
http://www.math.utah.edu/pub/bibnet/authors/s/shannonclaudeelwood.bib;
http://www.math.utah.edu/pub/tex/bib/bstj1950.bib;
http://www.math.utah.edu/pub/tex/bib/datacompression.bib",
note = "Reprinted in \cite{Slepian:1974:KPD}.",
URL = "http://bstj.belllabs.com/BSTJ/images/Vol30/bstj30150.pdf;
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abstract = "A new method of estimating the entropy and redundancy
of a language is described. This method exploits the
knowledge of the language statistics possessed by those
who speak the language, and depends on experimental
results in prediction of the next letter when the
preceding text is known. Results of experiments in
prediction are given, and some properties of an ideal
predictor are developed.",
acknowledgement = ackds # " and " # acknhfb,
attnote = "Included in Part A.",
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note = "Also published in/as: File Organization, Siwerts and
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abstract = "The ``information explosion'' noted in recent years
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information be kept to a minimum. A fully automatic and
rapid threepart compressor which can be used with
``any'' body of information to greatly reduce slow
external storage requirements and to increase the rate
of information transmission through a computer is
described in this paper. The system will also
automatically decode the compressed information on an
itembyitem basis when it is required. The three
component compressors, which can be used separately to
accomplish their specific tasks, are discussed: NUPAK
for the automatic compression of numerical data, ANPAK
for the automatic compression of ``any'' information,
and IOPAK for further compression of information to be
stored on tape or cards.",
acknowledgement = acknhfb,
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>Y '3'1 {5E1;1 mastersthesisdatacompression.bibTsui:1972:DCPStephen S. T. TsuiData Compression with Particular Applications to Video SignalsM.Eng.Department of Electrical Engineering, McGill UniversityMontreal, QC, Canadaiii + 151dec121972Mon Jan 28 15:10:29 MST 2013amicus.nlcbnc.ca:210/NL; http://www.math.utah.edu/pub/tex/bib/datacompression.bib2013.01.28 15:10:29 MSThttp://digitool.library.mcgill.ca/thesisfiȋ3=V 33;I;a57E};[;Iaarticledatacompression.bibSchalkwijk:1972:ASCJ. Pieter M. SchalkwijkAn Algorithm for Source CodingjIEEETRANSINFTHEORY183395399may51972IETTAWhttp://dx.doi.org/10.1109/TIT.1972.105483200189448 (print), 15579654 (electronic) OR 00189448 (print), 15579654 (electronic)00189448 OR 00189448Sat Jan 26 12:46:16 MST 2013http://www.math.utah.edu/pub/tession with Particular Applications to Video
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pages = "106",
year = "1973",
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}Gdu/pub/tex/bib/datacompression.bib2013.02.01 09:20:32 MSThttp://search.proquest.com/docview/302674792Electrical engineeringacknhfbRobert Tien Pei WangA Study of the Structure of Television Pictures as Applied to Practical Data Compression Techniques
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journal = jIEEETRANSCOMPUT,
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}ta compression by predictive coding. {II}.
Encoding algorithms",
journal = jIBMJRD,
volume = "18",
number = "2",
pages = "172179",
month = mar,
year = "1974",
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bibdate = "Tue Mar 25 14:26:59 MST 1997",
bibsource = "Compendex database;
http://www.math.utah.edu/pub/tex/bib/datacompression.bib;
http://www.math.utah.edu/pub/tex/bib/ibmjrd.bib",
abstract = "Predictive coding techniques for efficient
transmission or storage of twolevel (black and white)
digital images are examined. Algorithms for prediction
are discussed as well as coding techniques for encoding
the prediction error pattern. First, the authors survey
some schemes for encoding if the error pattern is
assumed to be memoryless. Then a method is developed
for encoding certain runlength distributions. Finally,
some experimental results for sample documents are
presented.",
acknowledgement = acknhfb,
classcodes = "B6120B (Codes); B6140 (Signal processing and
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fjournal = "IBM Journal of Research and Development",
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journalabr = "IBM J Res Dev",
keywords = "algorithms; applications of computers; codes,
symbolic; communication; communications applications of
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Filtering and Prediction Theory; predictive coding; two
level digital images; video signals",
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}Ib/datacompression.bib; http://www.math.utah.edu/pub/tex/bib/ibmjrd.bib1997.03.25 14:26:59 MSTPredictive coding techniques for efficient transmission or storage of twolevel (black and white) digital images are examined. Algorithms for prediction are discussed as well as coding techniques for encoding the prediction error pattern. First, the authors survey some schemes for encoding if the error pattern is assumed to be memoryless. Then a method is developed for encoding certain runlength distributions. Finally, some experimental results for sample documents are presented.IBM Journal of Research and Developmentalgorithms; applications of computers; codes, symbolic; communication; communications applications of computers; data compression; digital signals; encoding; image data compression; information theory  Filtering and Prediction Theory; predictive coding; two level digital images; video signalsacknhfbB6120B (Codes); B6140 (Signal processing and detection); C1260 (Information theory); C7410F (Communications computing)IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USAhttp://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5288520IBM J Res DevP Practical; X ExperimentalPredictive coding techniques for efficient transmission or storage of twolevel (black and white) digital images are examined. Algorithms for prediction are discussed as well as coding techniques for encoding the prediction error pattern. First, the authors survey some schemes for encoding if the error pattern is assumed to be memoryless. Then a method is developed for encoding certain runlength distributions. Finally, some experimental results for sample documents are presented.L. R. Bahl and H. KobayashiImage data compression by predictive coding. {II}. Encoding algorithms
@Article{Bahl:1974:IDC,
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for encoding certain runlength distributions. Finally,
some experimental results for sample documents are
presented.",
acknowledgement = acknhfb,
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4$JX 3'5%CC7;e5Qphdthesisdatacompression.bibFelt:1974:DCTDouglas Charles FeltDataCompression Techniques Using Adaptive TranslationPermutation CodesPh.D. thesisWashington State UniversityPullman, WA, USA1131974Fri Feb 1 09:5I_3'C57E;W[]y'CWCarticledatacompression.bibBahl:1974:IDCL. R. Bahl and H. KobayashiImage data compression by predictive coding. II. Encoding algorithmsjIBMJRD182172179mar31974IBMJAE00188646 (print), 21518556 (electronic) OR 00188646 (print), 21518556 (electronic)00188646 OR 00188646Tue Mar 25 14:26:59 MST 1997Compendex database; http://www.math.utah.edu/pub/tex/biion Techniques Using Adaptive
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pages = "113",
year = "1974",
bibdate = "Fri Feb 1 09:20:36 MST 2013",
bibsource = "http://search.proquest.com/;
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URL = "http://search.proquest.com/docview/302713192",
acknowledgement = acknhfb,
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}J20:36 MST 2013http://search.proquest.com/; http://www.math.utah.edu/pub/tex/bib/datacompression.bib2013.02.01 09:20:36 MSThttp://search.proquest.com/docview/302713192Computer scienceacknhfbDouglas Charles FeltDataCompression Techniques Using Adaptive TranslationPermutation Codes
@PhdThesis{Felt:1974:DCT,
author = "Douglas Charles Felt",
title = "DataCompression Techniques Using Adaptive
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school = "Washington State University",
address = "Pullman, WA, USA",
pages = "113",
year = "1974",
bibdate = "Fri Feb 1 09:20:36 MST 2013",
bibsource = "http://search.proquest.com/;
http://www.math.utah.edu/pub/tex/bib/datacompression.bib",
URL = "http://search.proquest.com/docview/302713192",
acknowledgement = acknhfb,
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}ession and Storage of Data",
journal = jCACM,
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number = "8",
pages = "434436",
month = aug,
year = "1974",
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ISSN = "00010782 (print), 15577317 (electronic)",
ISSNL = "00010782",
bibdate = "Mon Jan 22 06:47:50 MST 2001",
bibsource = "Compendex database;
ftp://ftp.ira.uka.de/pub/bibliography/Database/Wiederhold.bib;
http://dblp.unitrier.de/db/journals/cacm/cacm17.html#Hahn74;
http://www.math.utah.edu/pub/tex/bib/cacm1970.bib;
http://www.math.utah.edu/pub/tex/bib/datacompression.bib",
abstract = "This paper describes techniques that can, in most
cases, decrease storage size by a factor of from two to
four. The techniques involve special handling of
leading and trailing blanks, and the encoding of other
symbols in groups of fixed size as unique fixed point
numbers. The efficiency of the system is considered and
pertinent statistics are given and compared with
statistics for other information coding techniques.",
acknowledgement = acknhfb,
annote = "Generation of a character dictionary and its use to
minimize space.",
classcodes = "C6120 (File organisation); C6130 (Data handling
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classification = "731",
corpsource = "Univ. Waterloo, Ont., Canada",
fjournal = "Communications of the ACM",
journalURL = "http://portal.acm.org/browse_dl.cfm?idx=J79",
journalabr = "Commun ACM",
keywords = "coding techniques; compression; data handling; data
management; data storage; efficiency; encoding; file
maintenance; file organisation; fixed point numbers;
information coding techniques; information theory;
programs; text compression; utility",
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information block is represented by two subblocks
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title = ._03/tiff/243.tif; http://www3.oup.co.uk/computer_journal/hdb/Volume_18/Issue_03/tiff/244.tif; http://www3.oup.co.uk/computer_journal/hdb/Volume_18/Issue_03/tiff/245.tif; http://www3.oup.co.uk/computer_journal/hdb/Volume_18/Issue_03/tiff/246.tif; http://www3.oup.co.uk/computer_journal/hdb/Volume_18/Issue_03/tiff/247.tifThe Computer Journalaerospace applications of computers; data compression; ESRO 1; Hadamard; information theory; on ground compression; Run length method; satellite data; satellites; Shannon Fano method; transformationacknhfbB6140 (Signal processing and detection); C1260 (Information theory); C7490 (Computing in other engineering fields)Electrical Engng. Dept., Imperial Coll. of Sci. and Technol., London, UKhttp://comjnl.oxfordjournals.org/A Application; P PracticalL. F. TurnerThe `onground' compression of satellite data
@Article{Turner:1975:GCS,
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5V[ 3+%g_57CS;5qOA%gUarticledatacompression.bibTurner:1975:GCSL. F. TurnerThe `onground' compression of satellite datajCOMPJ183243247aug81975CMPJA6http://dx.doi.org/10.1093/comjnl/18.3.24300104620 (print), 14602067 (electronic) OR 00104620 (print), 14602067 (electronic)00104620 OR 00104620Tue Dec 4 14:47:56 MST 2012Compendex database; http://comjnl.oxfordjournals.org/content/18/3.toc; http://www.math.utah.edu/pub/tex/bib/compj.bib; http://www.math.utah.edu/pub/tex/bib/compj1970.bib; http://www.math.utah.edu/pub/tex/bib/datacompression.bib; http://www3.oup.co.uk/computer_journal/hdb/Volume_18/Issue_03/2012.12.04 14:47:56 MSThttp://comjnl.oxfordjournals.org/content/18/3/243.full.pdf+html; http://www3.oup.co.uk/computer_journal/hdb/Volume_18/Issue Code Data Compression: a Rate Distortion
Theoretic Approach",
type = "{Ph.D.} thesis",
school = "University of Southern California",
address = "Los Angeles, CA, USA",
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eeEU'3)CE'C};CEw inproceedingsdatacompression.bibGamal:1984:IDCA. El Gamal and A. OrlitskyInteractive Data CompressionIEEE:1984:ASF1001081984Thu Apr 5 06:13:39 MDT 2001http://www.math.utah.edu/pub/tex/bib/datacompression.bib2001.04.05 06:13:39 MDTacknhfbA. El Gamal and A. OrlitskyInteractive Data Compression
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crossref = "IEEE:1984:ASF",
pages = "100108",
year = "1984",
bibdate = "Thu Apr 5 06:13:39 MDT 2001",
bibsource = "http://www.math.utah.edu/pub/tex/bib/datacompression.bib",
acknowledgement = acknhfb,
}ength coding for graylevel
pictures",
journal = jATTBELLLABTECHJ,
volume = "63",
number = "2",
pages = "249260",
year = "1984",
CODEN = "ABLJER",
ISSN = "0748612X",
bibdate = "Fri Nov 12 09:17:39 2010",
bibsource = "Compendex database;
http://www.math.utah.edu/pub/tex/bib/bstj1980.bib;
http://www.math.utah.edu/pub/tex/bib/datacompression.bib",
abstract = "This paper presents a new variablelength coding
algorithm for bitrate reduction of digital images. The
coding scheme is based on the fact that by taking into
account the local conditional statistics of the
picture, the coding efficiency can be improved
considerably. Results of computer simulations are
presented in terms of picture quality and required bit
rate. Simulations show that for various Differential
Pulse Code Modulation (DPCM) coded pictures, coding
efficiency is such that a bit rate below the entropy of
the DPCM quantizer output is attained. For a 3bit DPCM
encoded picture, a bit rate of 1.64 bits/picture
element is achieved.",
acknowledgement = acknhfb,
fjournal = "AT\&T Bell Laboratories Technical Journal",
keywords = "data processing  code converters; pulse code
modulation",
subject = "conditional variablelength coding; digital image
reduction; graylevel picture coding",
topic = "image processing",
}mulations are presented in terms of picture quality and required bit rate. Simulations show that for various Differential Pulse Code Modulation (DPCM) coded pictures, coding efficiency is such that a bit rate below the entropy of the DPCM quantizer output is attained. For a 3bit DPCM encoded picture, a bit rate of 1.64 bits/picture element is achieved.AT&T Bell Laboratories Technical Journaldata processing  code converters; pulse code modulationconditional variablelength coding; digital image reduction; graylevel picture codingacknhfbThis paper presents a new variablelength coding algorithm for bitrate reduction of digital images. The coding scheme is based on the fact that by taking into account the local conditional statistics of the picture, the coding efficiency can be improved considerably. Results of computer simulations are presented in terms of picture quality and required bit rate. Simulations show that for various Differential Pulse Code Modulation (DPCM) coded pictures, coding efficiency is such that a bit rate below the entropy of the DPCM quantizer output is attained. For a 3bit DPCM encoded picture, a bit rate of 1.64 bits/picture element is achieved.H. GharaviConditional variablelength coding for graylevel pictures
@Article{Gharavi:1984:CVL,
author = "H. Gharavi",
title = "Conditional variablelength coding for graylevel
pictures",
journal = jATTBELLLABTECHJ,
volume = "63",
number = "2",
pages = "249260",
year = "1984",
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bibsource = "Compendex database;
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http://www.math.utah.edu/pub/tex/bib/datacompression.bib",
abstract = "This paper presents a new variablelength coding
algorithm for bitrate reduction of digital images. The
coding scheme is based on the fact that by taking into
account the local conditional statistics of the
picture, the coding efficiency can be improved
considerably. Results of computer simulations are
presented in terms of picture quality and required bit
rate. Simulations show that for various Differential
Pulse Code Modulation (DPCM) coded pictures, coding
efficiency is such that a bit rate below the entropy of
the DPCM quantizer output is attained. For a 3bit DPCM
encoded picture, a bit rate of 1.64 bits/picture
element is achieved.",
acknowledgement = acknhfb,
fjournal = "AT\&T Bell Laboratories Technical Journal",
keywords = "data processing  code converters; pulse code
modulation",
subject = "conditional variablelength coding; digital image
reduction; graylevel picture coding",
topic = "image processing",
}
uu@W 3%wE};{omiscdatacompression.bibISO:1984:IPSISOInformation Processing Systems  O?\ 3!77=;]9!articledatacompression.bibGharavi:1984:CVLH. GharaviConditional variablelength coding for graylevel picturesjATTBELLLABTECHJ6322492601984ABLJER0748612X OR 0748612XFri Nov 12 09:17:39 2010Compendex database; http://www.math.utah.edu/pub/tex/bib/bstj1980.bib; http://www.math.utah.edu/pub/tex/bib/datacompression.bib2010.11.12 09:17:39 ???This paper presents a new variablelength coding algorithm for bitrate reduction of digital images. The coding scheme is based on the fact that by taking into account the local conditional statistics of the picture, the coding efficiency can be improved considerably. Results of computer siata Communication
HighLevel Data Link Control ProcedureFrame Structure:
{IS 3309}",
edition = "Third",
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} MixedOrder Model Structures for Data
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type = "IBM research report",
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]BY 3)3O1m/=c;3#%3Ophdthesisdatacompression.bibLiang:1984:WHPFranklin Mark LiangWord Hyphenation by ComputerPh.D. dissertationComputer Science Department, Stanford UniversityStanford, CA, USA92mar31984Fri Jul 08 14:48:58 2005http://www.math.utah.edu/pub/tex/bib/datacompression.bib; http://www.math.utah.edu/pub/tex/bib/texbook3.bib2005.07.08 14:48:58 ???http://www.tug.org/docs/liang/; http://wwwlib.umi.com/dissertations/fulbAW !3+
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/techreportdatacompression.bibLangdon:1984:PVMGlen G. LangdonOn Parsing vs. MixedOrder Model Structures for Data CompressionIBM research reportation by Computer",
type = "{Ph.D.} dissertation",
school = "Computer Science Department, Stanford University",
address = "Stanford, CA, USA",
pages = "92",
month = mar,
year = "1984",
bibdate = "Fri Jul 08 14:48:58 2005",
bibsource = "http://www.math.utah.edu/pub/tex/bib/datacompression.bib;
http://www.math.utah.edu/pub/tex/bib/texbook3.bib",
URL = "http://www.tug.org/docs/liang/;
http://wwwlib.umi.com/dissertations/fullcit/8329742",
abstract = "This thesis describes research leading to an improved
word hyphenation algorithm for the T(,E)X82 typesetting
system. Hyphenation is viewed primarily as a data
compression problem, where we are given a dictionary of
words with allowable division points, and try to devise
methods that take advantage of the large amount of
redundancy present. The new hyphenation algorithm is
based on the idea of hyphenating and inhibiting
patterns. These are simply strings of letters that,
when they match in a word, give us information about
hyphenation at some point in the pattern. For example,
`tion' and `cc' are good hyphenating patterns. An
important feature of this method is that a suitable set
of patterns can be extracted automatically from the
dictionary. In order to represent the set of patterns
in a compact form that is also reasonably efficient for
searching, the author has developed a new data
structure called a packed trie. This data structure
allows the very fast search times characteristic of
indexed tries, but in many cases it entirely eliminates
the wasted space for null links usually present in such
tries. We demonstrate the versatility and practical
advantages of this data structure by using a variant of
it as the critical component of the program that
generates the patterns from the dictionary. The
resulting hyphenation algorithm uses about 4500
patterns that compile into a packed trie occupying 25K
bytes of storage. These patterns find 89\% of the
hyphens in a pocket dictionary word list, with
essentially no error. By comparison, the uncompressed
dictionary occupies over 500K bytes.",
acknowledgement = acknhfb,
}lcit/8329742This thesis describes research leading to an improved word hyphenation algorithm for the T(,E)X82 typesetting system. Hyphenation is viewed primarily as a data compression problem, where we are given a dictionary of words with allowable division points, and try to devise methods that take advantage of the large amount of redundancy present. The new hyphenation algorithm is based on the idea of hyphenating and inhibiting patterns. These are simply strings of letters that, when they match in a word, give us information about hyphenation at some point in the pattern. For example, `tion' and `cc' are good hyphenating patterns. An important feature of this method is that a suitable set of patterns can be extracted automatically from the dictionary. In order to represent the set of patterns in a compact form that is also reasonably efficient for searching, the author has developed a new data structure called a packed trie. This data structure allows the very fast search times characteristic of indexed tries, but in many cases it entirely eliminates the wasted space for null links usually present in such tries. We demonstrate the versatility and practical advantages of this data structure by using a variant of it as the critical component of the program that generates the patterns from the dictionary. The resulting hyphenation algorithm uses about 4500 patterns that compile into a packed trie occupying 25K bytes of storage. These patterns find 89% of the hyphens in a pocket dictionary word list, with essentially no error. By comparison, the uncompressed dictionary occupies over 500K bytes.acknhfbThis thesis describes research leading to an improved word hyphenation algorithm for the T(,E)X82 typesetting system. Hyphenation is viewed primarily as a data compression problem, where we are given a dictionary of words with allowable division points, and try to devise methods that take advantage of the large amount of redundancy present. The new hyphenation algorithm is based on the idea of hyphenating and inhibiting patterns. These are simply strings of letters that, when they match in a word, give us information about hyphenation at some point in the pattern. For example, `tion' and `cc' are good hyphenating patterns. An important feature of this method is that a suitable set of patterns can be extracted automatically from the dictionary. In order to represent the set of patterns in a compact form that is also reasonably efficient for searching, the author has developed a new data structure called a packed trie. This data structure allows the very fast search times characteristic of indexed tries, but in many cases it entirely eliminates the wasted space for null links usually present in such tries. We demonstrate the versatility and practical advantages of this data structure by using a variant of it as the critical component of the program that generates the patterns from the dictionary. The resulting hyphenation algorithm uses about 4500 patterns that compile into a packed trie occupying 25K bytes of storage. These patterns find 89\% of the hyphens in a pocket dictionary word list, with essentially no error. By comparison, the uncompressed dictionary occupies over 500K bytes.Franklin Mark LiangWord Hyphenation by Computer
@PhdThesis{Liang:1984:WHP,
author = "Franklin Mark Liang",
title = "Word Hyphenation by Computer",
type = "{Ph.D.} dissertation",
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bibdate = "Fri Jul 08 14:48:58 2005",
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URL = "http://www.tug.org/docs/liang/;
http://wwwlib.umi.com/dissertations/fullcit/8329742",
abstract = "This thesis describes research leading to an improved
word hyphenation algorithm for the T(,E)X82 typesetting
system. Hyphenation is viewed primarily as a data
compression problem, where we are given a dictionary of
words with allowable division points, and try to devise
methods that take advantage of the large amount of
redundancy present. The new hyphenation algorithm is
based on the idea of hyphenating and inhibiting
patterns. These are simply strings of letters that,
when they match in a word, give us information about
hyphenation at some point in the pattern. For example,
`tion' and `cc' are good hyphenating patterns. An
important feature of this method is that a suitable set
of patterns can be extracted automatically from the
dictionary. In order to represent the set of patterns
in a compact form that is also reasonably efficient for
searching, the author has developed a new data
structure called a packed trie. This data structure
allows the very fast search times characteristic of
indexed tries, but in many cases it entirely eliminates
the wasted space for null links usually present in such
tries. We demonstrate the versatility and practical
advantages of this data structure by using a variant of
it as the critical component of the program that
generates the patterns from the dictionary. The
resulting hyphenation algorithm uses about 4500
patterns that compile into a packed trie occupying 25K
bytes of storage. These patterns find 89\% of the
hyphens in a pocket dictionary word list, with
essentially no error. By comparison, the uncompressed
dictionary occupies over 500K bytes.",
acknowledgement = acknhfb,
}ls, and Formal Languages",
journal = jCOMPUTERSANDGRAPHICS,
volume = "18",
number = "3",
pages = "110",
month = jul,
year = "1984",
CODEN = "CGRADI, CPGPBZ",
ISSN = "00978930 (print), 15584569 (electronic)",
ISSNL = "00978930",
bibdate = "Sat Jan 26 12:46:16 MST 2013",
bibsource = "Ai/alife.bib;
http://www.math.utah.edu/pub/bibnet/authors/m/mandelbrotbenoit.bib;
http://www.math.utah.edu/pub/tex/bib/datacompression.bib",
note = "Applications of formal grammars for generating graphic
fractals  ``graftals''  in the modeling of
plants.",
acknowledgement = ackds,
annote = "Graftals. Methods for displaying natural objects based
on formal language models are presented. In particular,
deterministic models are shown to exhibit sufficient
variety to be used in production graphic systems.",
fjournal = "Computer Graphics",
journalURL = "http://www.sciencedirect.com/science/journal/00978493",
keyword = "fractals; modelsgraphics; plants; automatatheory",
rawdata = "Smith, Alvy Ray (1984) ``Plants, Fractals and Formal
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xxauthor = "Alvy Ray Smith",
}graphic fractals  ``graftals''  in the modeling of plants.Computer GraphicsackdsGraftals. Methods for displaying natural objects based on formal language models are presented. In particular, deterministic models are shown to exhibit sufficient variety to be used in production graphic systems.http://www.sciencedirect.com/science/journal/00978493Alvy Ray {Smith III}Applications of formal grammars for generating graphic fractals  ``graftals''  in the modeling of plants.Plants, Fractals, and Formal Languages
@Article{Smith:1984:PFF,
author = "Alvy Ray {Smith III}",
title = "Plants, Fractals, and Formal Languages",
journal = jCOMPUTERSANDGRAPHICS,
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bibsource = "Ai/alife.bib;
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note = "Applications of formal grammars for generating graphic
fractals  ``graftals''  in the modeling of
plants.",
acknowledgement = ackds,
annote = "Graftals. Methods for displaying natural objects based
on formal language models are presented. In particular,
deterministic models are shown to exhibit sufficient
variety to be used in production graphic systems.",
fjournal = "Computer Graphics",
journalURL = "http://www.sciencedirect.com/science/journal/00978493",
keyword = "fractals; modelsgraphics; plants; automatatheory",
rawdata = "Smith, Alvy Ray (1984) ``Plants, Fractals and Formal
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22WDY 3))o!57Ek;S)oarticledatacompression.bibWelch:1984:THPTerry A. WelchA Technique for HighPerformance Data CompressionjCOMPUTER176819jun61984CPTRB4http://doi.ieeecomputersociety.org/10.1109/MC.1984.165915800189162 (print), 15580814 (electronic) OR 00189162 (print), 15580814 (electronic)0018916?CZ 3)1Y=)57E#;k/7w5kYi
articledatacompression.bibSmith:1984:PFFAlvy Ray Smith IIIPlants, Fractals, and Formal LanguagesjCOMPUTERSANDGRAPHICS183110jul71984CGRADI, CPGPBZ00978930 (print), 15584569 (electronic) OR 00978930 (print), 15584569 (electronic)00978930 OR 00978930Sat Jan 26 12:46:16 MST 2013Ai/alife.bib; http://www.math.utah.edu/pub/bibnet/authors/m/mandelbrotbenoit.bib; http://www.math.utah.edu/pub/tex/bib/datacompression.bib2013.01.26 12:46:16 MSTApplications of formal grammars for generating Performance Data Compression",
journal = jCOMPUTER,
volume = "17",
number = "6",
pages = "819",
month = jun,
year = "1984",
CODEN = "CPTRB4",
DOI = "http://doi.ieeecomputersociety.org/10.1109/MC.1984.1659158",
ISSN = "00189162 (print), 15580814 (electronic)",
ISSNL = "00189162",
bibdate = "Sat Jan 26 12:46:16 MST 2013",
bibsource = "http://www.math.utah.edu/pub/tex/bib/computer1980.bib;
http://www.math.utah.edu/pub/tex/bib/datacompression.bib",
acknowledgement = ackds # " and " # acknhfb,
fjournal = "Computer",
journalURL = "http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=2",
rawdata = "Welch, T. A. (1984) ``A Technique for HighPerformance
Data Compression,'' {\it IEEE Computer},
{\bf17}(6):819, June.",
remark = "This is the paper with the LempelZivWelch (LZW)
algorithm that led to the famous Unix
compress/decompress programs (and the {.Z} file
extension), written by Spence Thomas at the University
of Utah in June 1984. It builds on prior work by Ziv
and Lempel \cite{Ziv:1977:UAS,Ziv:19778CIS} in
19771978.\par
Welch (the inventor) and Sperry Corporation (the
employer) applied for (on 20 June 1983), and received
(on 10 December 1985), a United States Patent (No.
4,558,302) on the algorithm (see
\pathhttp://patft.uspto.gov/netacgi/nphParser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=/netahtml/srchnum.htm&r=1&f=G&l=50&s1=4,558,302.WKU.&OS=PN/4,558,302&RS=PN/4,558,302),
and Unisys (which acquired Sperry in 1986) has since
regulated its use through licensing fees, notably from
Compuserv for its use in the GIF image format
compression.\par
The LZW decoding algorithm is widely held to be
unencumbered by patents.\par
About 1990, Adobe Systems licensed the LZW compression
algorithm from Unisys for use in the LZWEncode operator
in the Level 2 of the PostScript page description
language, so PostScriptproducing programs are required
to have a Unisys license in order to produce data for
that operator. Aladdin Software, the creators of
ghostscript, chose not to license the patent, and
instead, developed a completely different compression
algorithm that just happens to be decompressable with
the LZW decompression algorithm.\par
According to Salomon \cite[p.~216]{Salomon:2000:DCC},
``The patent expires on 10 December 2002, or 20 June
2003, depending on whether the GATT agreements
grandfather in existing patents or no. The first date
is 17 years from issuance of the patent (old U.S. law),
and the second is 20 years from the date of first
filing (a GATT requirement).''\par
In 1992, the GNU Project countered with gzip/gunzip
(and the {.gz} file extension), based on patentfree
algorithms, with better compression performance, and by
2000, those utilities had largely replaced
compress/decompress for Internet archives. gunzip will
uncompress a {.Z} file, but gzip will not create such a
file because of the patent.\par
In 1996, Julian R. Seward developed the bzip2/bunzip2
programs (and the .bz2 file extension), believed to be
patent free, based on the BurrowsWheeler
blocksorting text compression algorithm, and Huffman
coding, obtaining even better compression than gzip,
but at the expense of considerably longer running
times. The Unisys patent (United States Patent No.
4,558,302 (1985), Japanese Patent Numbers 2,123,602 and
2,610,084, and patents in Canada, France, Germany,
Italy and the United Kingdom) and license is discussed
at \path=http://www.unisys.com/about__unisys/lzw/= (URL
accurate on 16Jan2003).\par
In 1995, a collaborative group developed the Portable
Network Graphics (PNG) image file format in reaction to
the patent restrictions on the GIF format; see
\cite{Crocker:1995:PPN,Roelofs:1999:PDG}.",
}2 OR 00189162Sat Jan 26 12:46:16 MST 2013http://www.math.utah.edu/pub/tex/bib/computer1980.bib; http://www.math.utah.edu/pub/tex/bib/datacompression.bib2013.01.26 12:46:16 MSTComputerThis is the paper with the LempelZivWelch (LZW) algorithm that led to the famous Unix compress/decompress programs (and the .Z file extension), written by Spence Thomas at the University of Utah in June 1984. It builds on prior work by Ziv and Lempel cite Ziv:1977:UAS,Ziv:19778CIS in 19771978.par Welch (the inventor) and Sperry Corporation (the employer) applied for (on 20 June 1983), and received (on 10 December 1985), a United States Patent (No. 4,558,302) on the algorithm (see path http://patft.uspto.gov/netacgi/nphParser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=/netahtml/srchnum.htm&r=1&f=G&l=50&s1=4,558,302.WKU.&OS=PN/4,558,302&RS=PN/4,558,302), and Unisys (which acquired Sperry in 1986) has since regulated its use through licensing fees, notably from Compuserv for its use in the GIF image format compression.par The LZW decoding algorithm is widely held to be unencumbered by patents.par About 1990, Adobe Systems licensed the LZW compression algorithm from Unisys for use in the LZWEncode operator in the Level 2 of the PostScript page description language, so PostScriptproducing programs are required to have a Unisys license in order to produce data for that operator. Aladdin Software, the creators of ghostscript, chose not to license the patent, and instead, developed a completely different compression algorithm that just happens to be decompressable with the LZW decompression algorithm.par According to Salomon cite [p.~216]Salomon:2000:DCC, ``The patent expires on 10 December 2002, or 20 June 2003, depending on whether the GATT agreements grandfather in existing patents or no. The first date is 17 years from issuance of the patent (old U.S. law), and the second is 20 years from the date of first filing (a GATT requirement).''par In 1992, the GNU Project countered with gzip/gunzip (and the .gz file extension), based on patentfree algorithms, with better compression performance, and by 2000, those utilities had largely replaced compress/decompress for Internet archives. gunzip will uncompress a .Z file, but gzip will not create such a file because of the patent.par In 1996, Julian R. Seward developed the bzip2/bunzip2 programs (and the .bz2 file extension), believed to be patent free, based on the BurrowsWheeler blocksorting text compression algorithm, and Huffman coding, obtaining even better compression than gzip, but at the expense of considerably longer running times. The Unisys patent (United States Patent No. 4,558,302 (1985), Japanese Patent Numbers 2,123,602 and 2,610,084, and patents in Canada, France, Germany, Italy and the United Kingdom) and license is discussed at path =http://www.unisys.com/about__unisys/lzw/= (URL accurate on 16Jan2003).par In 1995, a collaborative group developed the Portable Network Graphics (PNG) image file format in reaction to the patent restrictions on the GIF format; see cite Crocker:1995:PPN,Roelofs:1999:PDG.ackdshttp://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=2Terry A. WelchA Technique for HighPerformance Data Compression
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algorithm that led to the famous Unix
compress/decompress programs (and the {.Z} file
extension), written by Spence Thomas at the University
of Utah in June 1984. It builds on prior work by Ziv
and Lempel \cite{Ziv:1977:UAS,Ziv:19778CIS} in
19771978.\par
Welch (the inventor) and Sperry Corporation (the
employer) applied for (on 20 June 1983), and received
(on 10 December 1985), a United States Patent (No.
4,558,302) on the algorithm (see
\pathhttp://patft.uspto.gov/netacgi/nphParser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=/netahtml/srchnum.htm&r=1&f=G&l=50&s1=4,558,302.WKU.&OS=PN/4,558,302&RS=PN/4,558,302),
and Unisys (which acquired Sperry in 1986) has since
regulated its use through licensing fees, notably from
Compuserv for its use in the GIF image format
compression.\par
The LZW decoding algorithm is widely held to be
unencumbered by patents.\par
About 1990, Adobe Systems licensed the LZW compression
algorithm from Unisys for use in the LZWEncode operator
in the Level 2 of the PostScript page description
language, so PostScriptproducing programs are required
to have a Unisys license in order to produce data for
that operator. Aladdin Software, the creators of
ghostscript, chose not to license the patent, and
instead, developed a completely different compression
algorithm that just happens to be decompressable with
the LZW decompression algorithm.\par
According to Salomon \cite[p.~216]{Salomon:2000:DCC},
``The patent expires on 10 December 2002, or 20 June
2003, depending on whether the GATT agreements
grandfather in existing patents or no. The first date
is 17 years from issuance of the patent (old U.S. law),
and the second is 20 years from the date of first
filing (a GATT requirement).''\par
In 1992, the GNU Project countered with gzip/gunzip
(and the {.gz} file extension), based on patentfree
algorithms, with better compression performance, and by
2000, those utilities had largely replaced
compress/decompress for Internet archives. gunzip will
uncompress a {.Z} file, but gzip will not create such a
file because of the patent.\par
In 1996, Julian R. Seward developed the bzip2/bunzip2
programs (and the .bz2 file extension), believed to be
patent free, based on the BurrowsWheeler
blocksorting text compression algorithm, and Huffman
coding, obtaining even better compression than gzip,
but at the expense of considerably longer running
times. The Unisys patent (United States Patent No.
4,558,302 (1985), Japanese Patent Numbers 2,123,602 and
2,610,084, and patents in Canada, France, Germany,
Italy and the United Kingdom) and license is discussed
at \path=http://www.unisys.com/about__unisys/lzw/= (URL
accurate on 16Jan2003).\par
In 1995, a collaborative group developed the Portable
Network Graphics (PNG) image file format in reaction to
the patent restrictions on the GIF format; see
\cite{Crocker:1995:PPN,Roelofs:1999:PDG}.",
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{\bf I.4.2}: Computing Methodologies, IMAGE PROCESSING,
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ethods. bf I.4.2: Computing Methodologies, IMAGE PROCESSING, Compression (Coding), Exact coding.acknhfbhttp://portal.acm.org/browse_dl.cfm?idx=J79Hanan SametData structures for quadtree approximation and compression
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subject = "{\bf E.1}: Data, DATA STRUCTURES, Trees. {\bf E.4}:
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{\bf I.4.2}: Computing Methodologies, IMAGE PROCESSING,
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}fferent Methods Based on the {KarhunenLoeve}
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image processing; image transformation, space
frequency, digital; KarhunenLoeve expansion; pattern
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}9XThu Feb 6 18:44:11 MST 1997Compendex database; Graphics/rosenfeld/1985.bib; http://www.math.utah.edu/pub/tex/bib/cvgip.bib; http://www.math.utah.edu/pub/tex/bib/datacompression.bib1997.02.06 18:44:11 MSTComputer Vision, Graphics, and Image Processingdata compression; eigendata problem; image analysis; image processing; image transformation, space frequency, digital; KarhunenLoeve expansion; pattern recognition; signal processingacknhfbU LondonQueen Elizabeth Coll, Dep of Physics, London, Englhttp://www.sciencedirect.com/science/journal/0734189XComput Vision Graphics Image ProcessM. H. Savoji and R. E. BurgeOn Different Methods Based on the {KarhunenLoeve} Expansion and Used in Image Analysis
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22i[_3'})57E;[)wwEQ'G)1articledatacompression.bibTodd:1985:PRCStephen Todd and Glen G. Langdon, Jr. and Jorma RissanenParameter Reduction and Context Selection for Compression of GrayScale ImagesjIBMJRD292188193mar31985IBMJAE00188646 (print), 21518556 (electronic) OR 00188646 (print), 21518556 (electronic)00188646 OR 00188646Tue Mar 25 14:26:59 MST 1997Compendex database; http://www.math.utah.edu/pub/tex/bib/datacompression.bib; http://www.math.utah.edu/pub/tex/bib/ibmjrd.bib1997.03.25 14:26:59 MSTIn the compression of multilevel (color or gray) image d5ZY3+E777C?;k{qwUE;{articledatacompression.bibSavoji:1985:DMBM. H. Savoji and R. E. BurgeOn Different Methods Based on the KarhunenLoeve Expansion and Used in Image AnalysisjCVGIP292259269feb21985CVGPDB0734189X OR 0734189X0734189X OR 073418
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journal = jIBMJRD,
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number = "2",
pages = "188193",
month = mar,
year = "1985",
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ISSN = "00188646 (print), 21518556 (electronic)",
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bibdate = "Tue Mar 25 14:26:59 MST 1997",
bibsource = "Compendex database;
http://www.math.utah.edu/pub/tex/bib/datacompression.bib;
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abstract = "In the compression of multilevel (color or gray) image
data, effective compression is obtained economically by
judicial selection of the predictor and the
conditioning states or contexts which determine what
probability distribution to use for the prediction
error. The authors provide a costeffective approach to
the following two problems: (1) to reduce the number of
coding parameters to describe a distribution when
several contexts are involved, and (2) to choose
contexts for which variations in prediction error
distributions are expected. They solve Problem 1
(distribution description) by a partition of the range
of values of the outcomes into equivalence classes,
called buckets. The result is a special decomposition
of the error range. Costeffectiveness is achieved by
using the many contexts only to predict the bucket
(equivalence class) probabilities. They solve Problem 2
(economical contexts) by using the buckets of the
surrounding pixels as components of the conditioning
class. The bucket values have the desirable properties
needed for the error distributions.",
acknowledgement = acknhfb,
affiliation = "IBM, United Kingdom Scientific Cent, Winchester,
Engl",
affiliationaddress = "IBM, United Kingdom Scientific Cent, Winchester,
Engl",
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}ata, effective compression is obtained economically by judicial selection of the predictor and the conditioning states or contexts which determine what probability distribution to use for the prediction error. The authors provide a costeffective approach to the following two problems: (1) to reduce the number of coding parameters to describe a distribution when several contexts are involved, and (2) to choose contexts for which variations in prediction error distributions are expected. They solve Problem 1 (distribution description) by a partition of the range of values of the outcomes into equivalence classes, called buckets. The result is a special decomposition of the error range. Costeffectiveness is achieved by using the many contexts only to predict the bucket (equivalence class) probabilities. They solve Problem 2 (economical contexts) by using the buckets of the surrounding pixels as components of the conditioning class. The bucket values have the desirable properties needed for the error distributions.IBM Journal of Research and DevelopmentAnalysis; buckets; classes; coding; compression; conditioning class; context selection; data compression; encoding; equivalence; error distributions; grayscale images; image processing; parameter reduction; parameters; picture processing; prediction error distributionsacknhfbIBM, United Kingdom Scientific Cent, Winchester, EnglIBM, United Kingdom Scientific Cent, Winchester, EnglB6140C (Optical information, image and video signal processing); C1250 (Pattern recognition)IBM UK Sci. Centre, Winchester, UKhttp://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5288520IBM J Res DevT Theoretical or MathematicalIn the compression of multilevel (color or gray) image data, effective compression is obtained economically by judicial selection of the predictor and the conditioning states or contexts which determine what probability distribution to use for the prediction error. The authors provide a costeffective approach to the following two problems: (1) to reduce the number of coding parameters to describe a distribution when several contexts are involved, and (2) to choose contexts for which variations in prediction error distributions are expected. They solve Problem 1 (distribution description) by a partition of the range of values of the outcomes into equivalence classes, called buckets. The result is a special decomposition of the error range. Costeffectiveness is achieved by using the many contexts only to predict the bucket (equivalence class) probabilities. They solve Problem 2 (economical contexts) by using the buckets of the surrounding pixels as components of the conditioning class. The bucket values have the desirable properties needed for the error distributions.Stephen Todd and Glen G. {Langdon, Jr.} and Jorma RissanenParameter Reduction and Context Selection for Compression of GrayScale Images
@Article{Todd:1985:PRC,
author = "Stephen Todd and Glen G. {Langdon, Jr.} and Jorma
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abstract = "In the compression of multilevel (color or gray) image
data, effective compression is obtained economically by
judicial selection of the predictor and the
conditioning states or contexts which determine what
probability distribution to use for the prediction
error. The authors provide a costeffective approach to
the following two problems: (1) to reduce the number of
coding parameters to describe a distribution when
several contexts are involved, and (2) to choose
contexts for which variations in prediction error
distributions are expected. They solve Problem 1
(distribution description) by a partition of the range
of values of the outcomes into equivalence classes,
called buckets. The result is a special decomposition
of the error range. Costeffectiveness is achieved by
using the many contexts only to predict the bucket
(equivalence class) probabilities. They solve Problem 2
(economical contexts) by using the buckets of the
surrounding pixels as components of the conditioning
class. The bucket values have the desirable properties
needed for the error distributions.",
acknowledgement = acknhfb,
affiliation = "IBM, United Kingdom Scientific Cent, Winchester,
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affiliationaddress = "IBM, United Kingdom Scientific Cent, Winchester,
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} and Scaling for Networked
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number = "UIUCDCSR851201",
institution = "Dept. of Computer Science, University of Illinois at
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address = "Urbana, IL, USA",
pages = "v + 80",
month = apr,
year = "1985",
bibdate = "Wed Feb 28 15:00:20 MST 1996",
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acknowledgement = acknhfb,
annote = "Originally presented as the author's thesis (M.S.) 
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Tarjan and Victor K. Wei",
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search and on variablelength encodings of integers. We
prove that it never performs much worse than Huffman
coding and can perform substantially better;
experiments on real files show that its performance is
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Huffman coding takes two passes).",
acknowledgement = ackds # " and " # acknhfb,
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}3/toc/Abstracts/00010782/5688.htmlA data compression scheme that exploits locality of reference, such as occurs when words are used frequently over short intervals and then fall into long periods of disuse, is described. The scheme is based on a simple heuristic for selforganizing sequential search and on variablelength encodings of integers. We prove that it never performs much worse than Huffman coding and can perform substantially better; experiments on real files show that its performance is usually quite close to that of Huffman coding. Our scheme has many implementation advantages: it is simple, allows fast encoding and decoding, and requires only one pass over the data to be compressed (static Huffman coding takes two passes).Communications of the ACMalgorithms; experimentation; image information; measurement; performance; statistics; theorybf E.4: Data, CODING AND INFORMATION THEORY, Data compaction and compression. bf E.1: Data, DATA STRUCTURES, Lists.ackdsExploits locality of reference when w4ords are used frequently over short intervals; is based on a selforganizing search and on variablelength encodings of integers. Its performance is close to that of Huffman coding. Requires only one pass over the data.http://portal.acm.org/browse_dl.cfm?idx=J79A data compression scheme that exploits locality of reference, such as occurs when words are used frequently over short intervals and then fall into long periods of disuse, is described. The scheme is based on a simple heuristic for selforganizing sequential search and on variablelength encodings of integers. We prove that it never performs much worse than Huffman coding and can perform substantially better; experiments on real files show that its performance is usually quite close to that of Huffman coding. Our scheme has many implementation advantages: it is simple, allows fast encoding and decoding, and requires only one pass over the data to be compressed (static Huffman coding takes two passes).Jon Louis Bentley and Daniel D. Sleator and Rob5ert E. Tarjan and Victor K. WeiA Locally Adaptive Data Compression Scheme
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bibsource = "Compendex database; Graphics/rosenfeld/1986.bib;
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@Article{Bille:2009:IAS,
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