A percolating state selector for suffix-tree context models

Author

Bunton, Suzanne

Author_Institution

Washington Univ., USA

fYear

1997

fDate

25-27 Mar 1997

Firstpage

32

Lastpage

41

Abstract

This paper introduces into practice and empirically evaluates a set of techniques for information-theoretic state selection that have been developing in asymptotic results state selection, which actually implements the selection of an entire model from among a set of competing models, is performed at least trivially by all of the suffix-tree FSMs used for on-line probability estimation. The set of state-selection techniques presented combines orthogonally with the other sets of design options covered in the companion paper of Bunton (Proceedings Data Compression Conference, p.42, 1997)

Keywords

data compression; encoding; probability; state estimation; trees (mathematics); asymptotic results state selection; code length; data compression; information-theoretic state selection; online probability estimation; percolating state selector; state-selection techniques; stochastic complexity; suffix-tree FSM; suffix-tree context models; Context modeling; Costs; Counting circuits; Decoding; Degradation; Encoding; Measurement; Performance evaluation; State estimation; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Compression Conference, 1997. DCC '97. Proceedings

Conference_Location

Snowbird, UT

ISSN

1068-0314

Print_ISBN

0-8186-7761-9

Type

conf

DOI

10.1109/DCC.1997.581957

Filename

581957