A context tree weighting algorithm with a finite window

Willems and colleagues proposed the context tree weighting (CTW) method. It is a method for probability estimation, by which the tree source serving the standard model for the data compression is compressed optimally in the quadratic sense with a high computational efficiency, under the condition th...

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Vydáno v:Electronics & communications in Japan. Part 3, Fundamental electronic science Ročník 83; číslo 1; s. 21 - 30
Hlavní autoři: Sakaguchi, Hiroaki, Kawabata, Tsutomu
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York John Wiley & Sons, Inc 01.01.2000
Témata:
ISSN:1042-0967, 1520-6440
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Shrnutí:Willems and colleagues proposed the context tree weighting (CTW) method. It is a method for probability estimation, by which the tree source serving the standard model for the data compression is compressed optimally in the quadratic sense with a high computational efficiency, under the condition that the parameters are unknown and the model is unknown. This article intends to apply the CTW method to the nonstationary source, which is a problem that has not been investigated. A compression algorithm with a forgetting mechanism and with a finite window (FWCTW method) is proposed. As the first step, the CTW method in general is discussed. A lemma concerning inferior probability preservation is presented, which serves as a key to the various realization problems. Using that lemma, the validity of the realization of the FWCTW method is shown. Then, for the case of a stationary memoryless source, the redundancy has asymptotic optimality in regard to the window length. The effectiveness of the application to the general constant‐interval nonstationary tree source is shown by experiment. © 1999 Scripta Technica, Electron Comm Jpn Pt 3, 83(1): 21–30, 2000
Bibliografie:ark:/67375/WNG-RBT911W2-0
istex:167407F39521F138DCF0C5B13315C94152DDE475
ArticleID:ECJC3
ISSN:1042-0967
1520-6440
DOI:10.1002/(SICI)1520-6440(200001)83:1<21::AID-ECJC3>3.0.CO;2-X