Concise, easy-to-read guide, introducing beginners to the engineering background of modern communication systems, from mobile phones to data storage.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Stefan M. Moser received the diploma (MSc) in electrical engineering in 1999, the MSc degree in industrial management (MBA) in 2003, and the PhD (Dr. sc. techn.) in the field of information theory in 2004, all from ETH Zurich, Switzerland. From 1999 to 2003 he was a Research and Teaching Assistant, and from 2004 to 2005 a Senior Research Assistant, with the Signal and Information Processing Laboratory at ETH Zurich. From 2005 to 2013, he was a Professor with the Department of Electrical and Computer Engineering at National Chiao Tung University (NCTU), Hsinchu, Taiwan. Currently he is a Senior Researcher with the Signal and Information Processing Laboratory at ETH Zurich and an Adjunct Professor at National Chiao Tung University. His research interests are in information theory and digital communications. Dr Moser was the recipient of the Wu Ta-You Memorial Award by the National Science Council of Taiwan in 2012, and the Best Paper Award for Young Scholars by the IEEE Communications Society Taipei and Tainan Chapters and the IEEE Information Theory Society Taipei Chapter in 2009. Further, he has received various awards from the National Chiao Tung University, two awards for outstanding teaching (in 2007 and 2012), and was presented with the Willi Studer Award of ETH and the ETH Medal (both in 1999), and the Sandoz (Novartis) Basler Maturandenpreis (1993).
Inhaltsangabe
1. Introduction Chung-Hsuan Wang 2. Error-detecting codes Chung-Hsuan Wang 3. Repetition and hamming codes Francis Lu 4. Data compression: efficient coding of a random message 5. Entropy and Shannon's source coding theorem 6. Mutual information and channel capacity Jwo-Yuh Wu 7. Achieving the Shannon limit by turbo coding 8. Other aspects of coding theory Francis Lu.
1. Introduction Chung-Hsuan Wang 2. Error-detecting codes Chung-Hsuan Wang 3. Repetition and hamming codes Francis Lu 4. Data compression: efficient coding of a random message 5. Entropy and Shannon's source coding theorem 6. Mutual information and channel capacity Jwo-Yuh Wu 7. Achieving the Shannon limit by turbo coding 8. Other aspects of coding theory Francis Lu.
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