Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities (Paperback)

This self-contained tutorial presents a unified treatment of single- and multi-user problems in Shannon's information theory considering in particular the cases that depart from the requirement that the error probability decays asymptotically in the blocklength. Instead, the error probabilities for various problems are bounded above by a non-vanishing constant and the spotlight is shone on achievable coding rates as functions of the growing blocklengths. This represents the study of asymptotic estimates with non-vanishing error probabilities. Divided into three parts, the monograph begins with an introduction to binary hypothesis testing. From there the author develops the theme for point-to-point communication systems. Finally, Network Information Theory problems such as channels with random state, the multiple-encoder distributed lossless source coding (Slepian-Wolf) problem and special cases of the Gaussian interference and multiple-access channels are considered. The monograph is written in a didactic nature that makes it accessible for students, researchers and engineers building practical communication systems.

General

Imprint:	Now Publishers Inc
Country of origin:	United States
Series:	Foundations and Trends (R) in Theoretical Computer Science
Release date:	September 2014
First published:	2014
Authors:	Vincent y F Tan • Aaron Roth
Dimensions:	234 x 156 x 11mm (L x W x T)
Format:	Paperback
Pages:	208
ISBN-13:	978-1-60198-852-2
Categories:	Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Computing & IT > Applications of computing > Databases > Data capture & analysis Promotions
LSN:	1-60198-852-4
Barcode:	9781601988522

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