Adaptive arithmetic coding using fuzzy reasoning and grey prediction

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Arithmetic coding is an attractive technique for lossless data compression. The most important thing in arithmetic coding is to construct a good modeler that always provides accurate probability estimation for incoming data. However, the characteristics of various types of source data bear a lot of uncertainty and are hard to be extracted, so we integrate fuzzy logic and grey theory to develop a smart fuzzy-grey-tuning modeler to deal with the problem of probability estimation. The average compression efficiency of the proposed method is better than other lossless compression methods, such as the Huffman, the approximate arithmetic, and the Lempel-Ziv, for three types of source data: text files, image files and binary files. Besides, the design is simple, fast, and suitable for VLSI implementation since an efficient table-look-up approach is adopted.

Original languageEnglish
Pages (from-to)239-254
Number of pages16
JournalFuzzy Sets and Systems
Volume114
Issue number2
DOIs
Publication statusPublished - 2000 Sep 1

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Arithmetic Coding
Fuzzy Reasoning
Lossless Compression
Prediction
Data compression
Grey Theory
Fuzzy logic
Tuning
Look-up Table
Data Compression
Thing
Fuzzy Logic
Compression
Integrate
Binary
Uncertainty

All Science Journal Classification (ASJC) codes

  • Logic
  • Artificial Intelligence

Cite this

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Adaptive arithmetic coding using fuzzy reasoning and grey prediction. / Chen, Pei-Yin; Jou, Jer-Min.

In: Fuzzy Sets and Systems, Vol. 114, No. 2, 01.09.2000, p. 239-254.

Research output: Contribution to journalArticle

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