Entropy of a bit-shift channel

Stan Baggen; Vladimir Balakirsky; Dee Denteneer; Sebastian Egner; Henk Hollmann; Ludo Tolhuizen; Evgeny Verbitskiy

Entropy of a bit-shift channel

Stan Baggen, Vladimir Balakirsky, Dee Denteneer, Sebastian Egner, Henk Hollmann, Ludo Tolhuizen, Evgeny Verbitskiy

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Abstract

We consider a simple transformation (coding) of an iid source called a bit-shift channel. This simple transformation occurs naturally in magnetic or optical data storage. The resulting process is not Markov of any order. We discuss methods of computing the entropy of the transformed process, and study some of its properties.

Original language	English
Title of host publication	EPRINTS-BOOK-TITLE
Publisher	University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science
Number of pages	12
Publication status	Published - 2006

Keywords

Gibbs vs. non-Gibbs
channel capacity
Entropy
Markov and hidden Markov processes

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keywords = "Gibbs vs. non-Gibbs, channel capacity, Entropy, Markov and hidden Markov processes",

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T1 - Entropy of a bit-shift channel

AU - Baggen, Stan

AU - Balakirsky, Vladimir

AU - Denteneer, Dee

AU - Egner, Sebastian

AU - Hollmann, Henk

AU - Tolhuizen, Ludo

AU - Verbitskiy, Evgeny

N1 - Relation: http://www.rug.nl/informatica/organisatie/overorganisatie/iwi Rights: University of Groningen. Research Institute for Mathematics and Computing Science (IWI)

PY - 2006

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N2 - We consider a simple transformation (coding) of an iid source called a bit-shift channel. This simple transformation occurs naturally in magnetic or optical data storage. The resulting process is not Markov of any order. We discuss methods of computing the entropy of the transformed process, and study some of its properties.

AB - We consider a simple transformation (coding) of an iid source called a bit-shift channel. This simple transformation occurs naturally in magnetic or optical data storage. The resulting process is not Markov of any order. We discuss methods of computing the entropy of the transformed process, and study some of its properties.

KW - Gibbs vs. non-Gibbs

KW - channel capacity

KW - Entropy

KW - Markov and hidden Markov processes

M3 - Chapter

BT - EPRINTS-BOOK-TITLE

PB - University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science

ER -

Entropy of a bit-shift channel

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Keywords

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