Results 1 
4 of
4
Code and parse trees for lossless source encoding
 Communications in Information and Systems
, 2001
"... This paper surveys the theoretical literature on fixedtovariablelength lossless source code trees, called code trees, and on variablelengthtofixed lossless sounce code trees, called parse trees. Huffman coding [ l] is the most well known code tree problem, but there are a number of interestin ..."
Abstract

Cited by 61 (1 self)
 Add to MetaCart
This paper surveys the theoretical literature on fixedtovariablelength lossless source code trees, called code trees, and on variablelengthtofixed lossless sounce code trees, called parse trees. Huffman coding [ l] is the most well known code tree problem, but there are a number of interesting variants of the problem formulation which lead to other combinatorial optimization problems. Huffman coding as an
Lightweight natural language text compression. Information Retrieval
, 2007
"... Variants of Huffman codes where words are taken as the source symbols are currently the most attractive choices to compress natural language text databases. In particular, Tagged Huffman Code by Moura et al. offers fast direct searching on the compressed text and random access capabilities, in excha ..."
Abstract

Cited by 40 (30 self)
 Add to MetaCart
(Show Context)
Variants of Huffman codes where words are taken as the source symbols are currently the most attractive choices to compress natural language text databases. In particular, Tagged Huffman Code by Moura et al. offers fast direct searching on the compressed text and random access capabilities, in exchange for producing around 11 % larger compressed files. This work describes EndTagged Dense Code and (s, c)Dense Code, two new semistatic statistical methods for compressing natural language texts. These techniques permit simpler and faster encoding and obtain better compression ratios than Tagged Huffman Code, while maintaining its fast direct search and random access capabilities. We show that Dense Codes improve Tagged Huffman Code compression ratio by about 10%, reaching only 0.6% overhead over the optimal Huffman compression ratio. Being simpler, Dense Codes are generated 45% to 60 % faster than Huffman codes. This makes Dense Codes a very attractive alternative to Huffman code variants for various reasons: they are simpler to program, faster to build, of almost optimal size, and as fast and easy to search as the best Huffman variants, which are not so close to the optimal size.
Robust Universal Complete Codes for Transmission and Compression
 Discrete Applied Mathematics
, 1996
"... Several measures are defined and investigated, which allow the comparison of codes as to their robustness against errors. Then new universal and complete sequences of variablelength codewords are proposed, based on representing the integers in a binary Fibonacci numeration system. Each sequence is ..."
Abstract

Cited by 16 (5 self)
 Add to MetaCart
(Show Context)
Several measures are defined and investigated, which allow the comparison of codes as to their robustness against errors. Then new universal and complete sequences of variablelength codewords are proposed, based on representing the integers in a binary Fibonacci numeration system. Each sequence is constant and need not be generated for every probability distribution. These codes can be used as alternatives to Huffman codes when the optimal compression of the latter is not required, and simplicity, faster processing and robustness are preferred. The codes are compared on several "reallife" examples. 1. Motivation and Introduction Let A = fA 1 ; A 2 ; \Delta \Delta \Delta ; An g be a finite set of elements, called cleartext elements, to be encoded by a static uniquely decipherable (UD) code. For notational ease, we use the term `code' as abbreviation for `set of codewords'; the corresponding encoding and decoding algorithms are always either given or clear from the context. A code i...
unknown title
"... This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal noncommercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or sel ..."
Abstract
 Add to MetaCart
(Show Context)
This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal noncommercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit: