### 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 |
---|---|

Title of host publication | 2009 IEEE International Symposium on Information Theory, ISIT 2009 |

Pages | 719-723 |

Number of pages | 5 |

DOIs | |

Publication status | Published - 2009 Nov 19 |

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

### Publication series

Name | IEEE International Symposium on Information Theory - Proceedings |
---|---|

ISSN (Print) | 2157-8102 |

### Conference

Conference | 2009 IEEE International Symposium on Information Theory, ISIT 2009 |
---|---|

Country | Korea, Republic of |

City | Seoul |

Period | 09/6/28 → 09/7/3 |

### ASJC Scopus subject areas

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

## Fingerprint Dive into the research topics of 'Reducing the space complexity of a bayes coding algorithm using an expanded context tree'. Together they form a unique fingerprint.

## Cite this

*2009 IEEE International Symposium on Information Theory, ISIT 2009*(pp. 719-723). [5205677] (IEEE International Symposium on Information Theory - Proceedings). https://doi.org/10.1109/ISIT.2009.5205677