Information Theory for Electrical Engineers / Signals and Communication Technology (PDF)
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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.
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.
- Autor: Orhan Gazi
- 2018, 1st ed. 2018, 276 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 9811084327
- ISBN-13: 9789811084324
- Erscheinungsdatum: 09.03.2018
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 6.04 MB
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