This new and updated textbook is an excellent way to introduce probability and information theory to students new to mathematics, computer science, engineering, statistics, economics, or business studies. Only requiring knowledge of basic calculus, it begins by building a clear and systematic foundation to probability and information. Classic topics covered include discrete and continuous random variables, entropy and mutual information, maximum entropy methods, the central limit theorem and the coding and transmission of information. Newly covered for this edition is modern material on Markov chains and their entropy. Examples and exercises are included to illustrate how to use the theory in a wide range of applications, with detailed solutions to most exercises available online for instructors.Read more
- Integrated approach to probability and information suitable for pure or applied students
- Illustrates a wide range of applications in science and mathematics
- Modern, rigorous approach that needs only a background in basic calculus
Reviews & endorsements
"... the writing is authoritative, and well-tailored to the intended readership. Places where more advanced mathematics is required are indicated clearly, the illustrative material is well-chosen. Any lecturer seeking a text, at this level, to recommend to students, should give this book serious consideration."
John Haigh for Significance
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- Edition: 2nd Edition
- Date Published: September 2008
- format: Paperback
- isbn: 9780521727884
- length: 290 pages
- dimensions: 247 x 174 x 14 mm
- weight: 0.59kg
- contains: 65 b/w illus. 3 tables 240 exercises
- availability: Available
Table of Contents
Preface to the first edition
Preface to the second edition
3. Sets and measures
5. Discrete random variables
6. Information and entropy
8. Random variables with probability density functions
9. Random vectors
10. Markov chains and their entropy
Appendix 1. Proof by mathematical induction
Appendix 2. Lagrange multipliers
Appendix 3. Integration of exp (-½x²)
Appendix 4. Table of probabilities associated with the standard normal distribution
Appendix 5. A rapid review of Matrix algebra
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