A fast and efficient lossless data-compression method

Jer Min Jou; Pei Yin Chen

doi:10.1109/26.789659

A fast and efficient lossless data-compression method

Jer Min Jou, Pei Yin Chen

研究成果: Article › 同行評審

11 引文斯高帕斯（Scopus）

摘要

This paper describes an online lossless datacompression method using adaptive arithmetic coding. To achieve good compression efficiency, we employ an adaptive fuzzy-tuning modeler that applies fuzzy inference to deal efficiently with the problem of conditional probability estimation. In comparison with other lossless coding schemes, the compression results of the proposed method are good and satisfactory for various types of source data. Since we adopt the table-lookup approach for the fuzzy-tuning modeler, the design is simple, fast, and suitable for VLSI implementation.

原文	English
頁（從 - 到）	1278-1283
頁數	6
期刊	IEEE Transactions on Communications
卷	47
發行號	9
DOIs	https://doi.org/10.1109/26.789659
出版狀態	Published - 1999

All Science Journal Classification (ASJC) codes

電氣與電子工程

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10.1109/26.789659

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note = "Funding Information: Paper approved by C. S. Ravishankar, the Editor for Speech Processing of the IEEE Communications Society. Manuscript received November 5, 1997; revised June 15, 1998 and December 23, 1998. This research was supported in part by the National Science Council, R.O.C., under Grant NSC-86-2221-E-006-022.",

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N2 - This paper describes an online lossless datacompression method using adaptive arithmetic coding. To achieve good compression efficiency, we employ an adaptive fuzzy-tuning modeler that applies fuzzy inference to deal efficiently with the problem of conditional probability estimation. In comparison with other lossless coding schemes, the compression results of the proposed method are good and satisfactory for various types of source data. Since we adopt the table-lookup approach for the fuzzy-tuning modeler, the design is simple, fast, and suitable for VLSI implementation.

AB - This paper describes an online lossless datacompression method using adaptive arithmetic coding. To achieve good compression efficiency, we employ an adaptive fuzzy-tuning modeler that applies fuzzy inference to deal efficiently with the problem of conditional probability estimation. In comparison with other lossless coding schemes, the compression results of the proposed method are good and satisfactory for various types of source data. Since we adopt the table-lookup approach for the fuzzy-tuning modeler, the design is simple, fast, and suitable for VLSI implementation.

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A fast and efficient lossless data-compression method

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