On approximate pattern matching for a class of gibbs random fields

Jean Rene Chazottes; Frank Redig; Evgeny Verbitskiy

doi:10.1214/105051605000000827

On approximate pattern matching for a class of gibbs random fields

Jean Rene Chazottes
, Frank Redig
, Evgeny Verbitskiy

Research output: Contribution to journal › Article › peer-review

Abstract

We prove an exponential approximation for the law of approximate occurrence of typical patterns for a class of Gibssian sources on the lattice ℤ ^d, d ≥ 2. From this result, we deduce a law of large numbers and a large deviation result for the waiting time of distorted patterns.

Original language	English
Pages (from-to)	670-684
Number of pages	15
Journal	Annals of Applied Probability
Volume	16
Issue number	2
DOIs	https://doi.org/10.1214/105051605000000827
Publication status	Published - 1 May 2006

Keywords

Exponential law
Hitting time
Large deviations
Rate distortion

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10.1214/105051605000000827

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title = "On approximate pattern matching for a class of gibbs random fields",

abstract = "We prove an exponential approximation for the law of approximate occurrence of typical patterns for a class of Gibssian sources on the lattice ℤ d, d ≥ 2. From this result, we deduce a law of large numbers and a large deviation result for the waiting time of distorted patterns.",

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AU - Redig, Frank

AU - Verbitskiy, Evgeny

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AB - We prove an exponential approximation for the law of approximate occurrence of typical patterns for a class of Gibssian sources on the lattice ℤ d, d ≥ 2. From this result, we deduce a law of large numbers and a large deviation result for the waiting time of distorted patterns.

KW - Exponential law

KW - Hitting time

KW - Large deviations

KW - Rate distortion

UR - https://www.scopus.com/pages/publications/33746882500

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DO - 10.1214/105051605000000827

M3 - Article

AN - SCOPUS:33746882500

SN - 1050-5164

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EP - 684

JO - Annals of Applied Probability

JF - Annals of Applied Probability

IS - 2

ER -

On approximate pattern matching for a class of gibbs random fields

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Keywords

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