Estimating the Information Rate of Noisy Two-Dimensional Constrained Channels


METADATA ONLY

Date

2010

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

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Abstract

The problem of computing the information rate of noisy two-dimensional constrained source/channel models has been an unsolved problem. In this paper, we propose two Monte Carlo methods for this problem. The first method, which is exact in expectation, combines tree-based Gibbs sampling with importance sampling. The second method uses generalized belief propagation and is shown to yield a good approximation of the information rate.

Publication status

published

Editor

Book title

2010 IEEE International Symposium on Information Theory

Journal / series

Volume

Pages / Article No.

1678 - 1682

Publisher

IEEE

Event

IEEE International Symposium on Information Theory (ISIT 2010)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

03568 - Loeliger, Hans-Andrea / Loeliger, Hans-Andrea check_circle

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