A Student's Guide to Coding and Information Theory
This easy-to-read guide provides a concise introduction to the engineering background of modern communication systems, from mobile phones to data compression and storage. Background mathematics and specific engineering techniques are kept to a minimum so that only a basic knowledge of high-school mathematics is needed to understand the material covered. The authors begin with many practical applications in coding, including the repetition code, the Hamming code and the Huffman code. They then explain the corresponding information theory, from entropy and mutual information to channel capacity and the information transmission theorem. Finally, they provide insights into the connections between coding theory and other fields. Many worked examples are given throughout the book, using practical applications to illustrate theoretical definitions. Exercises are also included, enabling readers to double-check what they have learned and gain glimpses into more advanced topics, making this perfect for anyone who needs a quick introduction to the subject.
- An easy-to-read introduction to the engineering background of modern communication systems
- Assumes only basic mathematical knowledge, making it ideal for students from a wide variety of subjects
- Includes many examples which link the theory covered to practical applications, as well as exercises at the end of each chapter
Reviews & endorsements
'The book is nicely written, and is recommended as a textbook for a one-semester introductory course on coding and information theory.' Pushpa N. Rathie, Zentralblatt MATH
Product details
January 2012Hardback
9781107015838
206 pages
235 × 157 × 15 mm
0.45kg
48 b/w illus. 29 tables 38 exercises
Available
Table of Contents
- 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.