1 / 2Information Theory
Information Theory is a textbook that develops core Shannon theory and connects it to statistical learning, computer science and modern communication theory. Its finite block-length approach, broad topic coverage and more than 210 end-of-part exercises suit structured study, while the substantial 748-page length is worth considering for portability.
At a glance
- Introduces classical Shannon information theory with a finite block-length approach.
- Covers data compression, channel coding and rate-distortion theory.
- Connects information-theoretic methods with statistical learning and computer science topics including f-divergences, PAC Bayes and Kolmogorov's metric entropy.
- The description reports more than 210 end-of-part exercises and examples.
- Additional standalone chapters address specialized information theory topics.
Reference price: $128.36
Price checked: Nov 13, 2026
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Pros and cons
Pros
- The described scope bridges foundational communication theory and applications in statistics, machine learning and computer science.
- Exercises and examples support use as a structured study text.
- The book is aimed at senior undergraduate and graduate students in electrical engineering, statistics and computer science.
Cons
- At 748 pages and a listed weight of 1.68 kg, it is a substantial volume to carry or work through.
Technical specifications
8 specifications| Publisher | Cambridge University Press |
|---|---|
| Publication date | Jan. 2 2025 |
| Language | English |
| Print length | 748 pages |
| ISBN-10 | 1108832903 |
| ISBN-13 | 978-1108832908 |
| Weight listed | 1.68 kg |
|---|---|
| Dimensions | 25.4 x 17.81 x 2.54 cm |
Who is it for?
A good fit for
- Senior undergraduate and graduate students studying information theory, electrical engineering, statistics or computer science.
- Readers seeking a single text that spans Shannon theory and selected statistical-learning applications.
Less suited to
- Readers seeking a brief overview or a lightweight book for frequent carrying.
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Frequently asked questions
What topics does Information Theory cover?
The description lists Shannon theory, data compression, channel coding and rate-distortion, as well as information-theoretic methods applied to statistical learning and computer science.
Who is this textbook intended for?
It is described as an introductory text for senior undergraduate and graduate students in electrical engineering, statistics and computer science.
Does the book include exercises?
The listing description reports more than 210 end-of-part exercises and numerous examples.
How large is the book?
The listed print length is 748 pages, with dimensions of 25.4 x 17.81 x 2.54 cm and a weight of 1.68 kg.
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