### Abstract

The context tree models are widely used in a lot of research fields. Patricia[7] like trees are applied to the context trees that are expanded according to the increase of the length of a source sequence in the previous researches of non-predictive source coding and model selection. The space complexity of the Patricia like context trees are O(t) where t is the length of a source sequence. On the other hand, the predictive Bayes source coding algorithm cannot use a Patricia like context tree, because it is difficult to hold and update the posterior probability parameters on a Patricia like tree. So the space complexity of the expanded trees in the predictive Bayes coding algorithm is O(t^{2}). In this paper, we propose an efficient predictive Bayes coding algorithm using a new representation of the posterior probability parameters and the compact context tree holding the parameters whose space complexity is O(t).

Original language | English |
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Title of host publication | IEEE International Symposium on Information Theory - Proceedings |

Pages | 719-723 |

Number of pages | 5 |

DOIs | |

Publication status | Published - 2009 |

Event | 2009 IEEE International Symposium on Information Theory, ISIT 2009 - Seoul Duration: 2009 Jun 28 → 2009 Jul 3 |

### Other

Other | 2009 IEEE International Symposium on Information Theory, ISIT 2009 |
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City | Seoul |

Period | 09/6/28 → 09/7/3 |

### Fingerprint

### ASJC Scopus subject areas

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

### Cite this

*IEEE International Symposium on Information Theory - Proceedings*(pp. 719-723). [5205677] https://doi.org/10.1109/ISIT.2009.5205677

**Reducing the space complexity of a bayes coding algorithm using an expanded context tree.** / Matsushima, Toshiyasu; Hirasawa, Shigeich.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*IEEE International Symposium on Information Theory - Proceedings.*, 5205677, pp. 719-723, 2009 IEEE International Symposium on Information Theory, ISIT 2009, Seoul, 09/6/28. https://doi.org/10.1109/ISIT.2009.5205677

}

TY - GEN

T1 - Reducing the space complexity of a bayes coding algorithm using an expanded context tree

AU - Matsushima, Toshiyasu

AU - Hirasawa, Shigeich

PY - 2009

Y1 - 2009

N2 - The context tree models are widely used in a lot of research fields. Patricia[7] like trees are applied to the context trees that are expanded according to the increase of the length of a source sequence in the previous researches of non-predictive source coding and model selection. The space complexity of the Patricia like context trees are O(t) where t is the length of a source sequence. On the other hand, the predictive Bayes source coding algorithm cannot use a Patricia like context tree, because it is difficult to hold and update the posterior probability parameters on a Patricia like tree. So the space complexity of the expanded trees in the predictive Bayes coding algorithm is O(t2). In this paper, we propose an efficient predictive Bayes coding algorithm using a new representation of the posterior probability parameters and the compact context tree holding the parameters whose space complexity is O(t).

AB - The context tree models are widely used in a lot of research fields. Patricia[7] like trees are applied to the context trees that are expanded according to the increase of the length of a source sequence in the previous researches of non-predictive source coding and model selection. The space complexity of the Patricia like context trees are O(t) where t is the length of a source sequence. On the other hand, the predictive Bayes source coding algorithm cannot use a Patricia like context tree, because it is difficult to hold and update the posterior probability parameters on a Patricia like tree. So the space complexity of the expanded trees in the predictive Bayes coding algorithm is O(t2). In this paper, we propose an efficient predictive Bayes coding algorithm using a new representation of the posterior probability parameters and the compact context tree holding the parameters whose space complexity is O(t).

UR - http://www.scopus.com/inward/record.url?scp=70449463512&partnerID=8YFLogxK

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U2 - 10.1109/ISIT.2009.5205677

DO - 10.1109/ISIT.2009.5205677

M3 - Conference contribution

AN - SCOPUS:70449463512

SN - 9781424443130

SP - 719

EP - 723

BT - IEEE International Symposium on Information Theory - Proceedings

ER -