Information Theory for Electrical Engineers

Lieferzeit: Lieferbar innerhalb 14 Tagen

90,94 

Signals and Communication Technology

ISBN: 9811084319
ISBN 13: 9789811084317
Autor: Gazi, Orhan
Verlag: Springer Verlag GmbH
Umfang: ix, 276 S., 120 s/w Illustr., 2 farbige Illustr., 276 p. 122 illus., 2 illus. in color.
Erscheinungsdatum: 19.03.2018
Auflage: 1/2018
Produktform: Gebunden/Hardback
Einband: Gebunden

This book explains the fundamental concepts of information theory, so as to help students better understand modern communication technologies. It was especially written for electrical and communication engineers working on communication subjects. The book especially focuses on the understandability of the topics, and accordingly uses simple and detailed mathematics, together with a wealth of solved examples. The book consists of four chapters, the first of which explains the entropy and mutual information concept for discrete random variables. Chapter 2 introduces the concepts of entropy and mutual information for continuous random variables, along with the channel capacity. In turn, Chapter 3 is devoted to the typical sequences and data compression. One of Shannon’s most important discoveries is the channel coding theorem, and it is critical for electrical and communication engineers to fully comprehend the theorem. As such, Chapter 4 solely focuses on it. To gain the most from the book, readers should have a fundamental grasp of probability and random variables; otherwise, they will find it nearly impossible to understand the topics discussed.

Artikelnummer: 3500414 Kategorie:

Beschreibung

This book explains the fundamental concepts of information theory, so as to help students better understand modern communication technologies. It was especially written for electrical and communication engineers working on communication subjects. The book especially focuses on the understandability of the topics, and accordingly uses simple and detailed mathematics, together with a wealth of solved examples.The book consists of four chapters, the first of which explains the entropy and mutual information concept for discrete random variables. Chapter 2 introduces the concepts of entropy and mutual information for continuous random variables, along with the channel capacity. In turn, Chapter 3 is devoted to the typical sequences and data compression. One of Shannons most important discoveries is the channel coding theorem, and it is critical for electrical and communication engineers to fully comprehend the theorem. As such, Chapter 4 solely focuses on it.To gain the most from the book, readers should have a fundamental grasp of probability and random variables; otherwise, they will find it nearly impossible to understand the topics discussed.

Autorenporträt

Orhan Gazi is an associate professor in electronic and communication engineering department, Cankaya University.He got his BS, MS, and PhD degrees all in electrical and electronics engineering from Middle East Technical University, Ankara-Turkey, in 1996, 2001, and 2007 respectively. His research area involves signal processing, information theory, and forward error correction. Recently he is studying on polar channel codes and preparing publications in this area.

Herstellerkennzeichnung:


Springer Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

E-Mail: juergen.hartmann@springer.com

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