### 抄録

The context tree weighting (CTW) algorithm [Willems et al., 1993] has high compressibility for universal coding with respect to FSMX sources. The present authors propose an algorithm by reinterpreting the CTW algorithm from the viewpoint of Bayes coding. This algorithm can be applied to a wide class of prior distribution for finite alphabet FSMX sources. The algorithm is regarded as both a generalized version of the CTW procedure and a practical algorithm using a context tree of the adaptive Bayes coding which has been studied in Mataushima et al. (1991). Moreover, the proposed algorithm is free from underflow which frequently occurs in the CTW procedure.

元の言語 | English |
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ホスト出版物のタイトル | IEEE International Symposium on Information Theory - Proceedings |

ページ | 386 |

ページ数 | 1 |

DOI | |

出版物ステータス | Published - 1994 |

イベント | 1994 IEEE International Symposium on Information Theory, ISIT 1994 - Trondheim 継続期間: 1994 6 27 → 1994 7 1 |

### Other

Other | 1994 IEEE International Symposium on Information Theory, ISIT 1994 |
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市 | Trondheim |

期間 | 94/6/27 → 94/7/1 |

### Fingerprint

### ASJC Scopus subject areas

- Applied Mathematics
- Modelling and Simulation
- Theoretical Computer Science
- Information Systems

### これを引用

*IEEE International Symposium on Information Theory - Proceedings*(pp. 386). [394633] https://doi.org/10.1109/ISIT.1994.394633

**A Bayes coding algorithm using context tree.** / Matsushima, Toshiyasu; Hirasawa, Shigeichi.

研究成果: Conference contribution

*IEEE International Symposium on Information Theory - Proceedings.*, 394633, pp. 386, 1994 IEEE International Symposium on Information Theory, ISIT 1994, Trondheim, 94/6/27. https://doi.org/10.1109/ISIT.1994.394633

}

TY - GEN

T1 - A Bayes coding algorithm using context tree

AU - Matsushima, Toshiyasu

AU - Hirasawa, Shigeichi

PY - 1994

Y1 - 1994

N2 - The context tree weighting (CTW) algorithm [Willems et al., 1993] has high compressibility for universal coding with respect to FSMX sources. The present authors propose an algorithm by reinterpreting the CTW algorithm from the viewpoint of Bayes coding. This algorithm can be applied to a wide class of prior distribution for finite alphabet FSMX sources. The algorithm is regarded as both a generalized version of the CTW procedure and a practical algorithm using a context tree of the adaptive Bayes coding which has been studied in Mataushima et al. (1991). Moreover, the proposed algorithm is free from underflow which frequently occurs in the CTW procedure.

AB - The context tree weighting (CTW) algorithm [Willems et al., 1993] has high compressibility for universal coding with respect to FSMX sources. The present authors propose an algorithm by reinterpreting the CTW algorithm from the viewpoint of Bayes coding. This algorithm can be applied to a wide class of prior distribution for finite alphabet FSMX sources. The algorithm is regarded as both a generalized version of the CTW procedure and a practical algorithm using a context tree of the adaptive Bayes coding which has been studied in Mataushima et al. (1991). Moreover, the proposed algorithm is free from underflow which frequently occurs in the CTW procedure.

UR - http://www.scopus.com/inward/record.url?scp=84894291840&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84894291840&partnerID=8YFLogxK

U2 - 10.1109/ISIT.1994.394633

DO - 10.1109/ISIT.1994.394633

M3 - Conference contribution

AN - SCOPUS:84894291840

SN - 0780320158

SN - 9780780320154

SP - 386

BT - IEEE International Symposium on Information Theory - Proceedings

ER -