Logo

Information Theory and Coding

Small book cover: Information Theory and Coding

Information Theory and Coding
by

Publisher: University of Cambridge
Number of pages: 75

Description:
The aims of this course are to introduce the principles and applications of information theory. The course will study how information is measured in terms of probability and entropy, and the relationships among conditional and joint entropies; how these are used to calculate the capacity of a communication channel, with and without noise; coding schemes, including error correcting codes; how discrete channels and measures of information generalize to their continuous forms; etc.

Home page url

Download or read it online for free here:
Download link
(1.4MB, PDF)

Similar books

Book cover: Around Kolmogorov Complexity: Basic Notions and ResultsAround Kolmogorov Complexity: Basic Notions and Results
by - arXiv.org
Algorithmic information theory studies description complexity and randomness. This text covers the basic notions of algorithmic information theory: Kolmogorov complexity, Solomonoff universal a priori probability, effective Hausdorff dimension, etc.
(6579 views)
Book cover: Algorithmic Information TheoryAlgorithmic Information Theory
by - CWI
We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain this quantitative approach to defining information and discuss the extent to which Kolmogorov's and Shannon's theory have a common purpose.
(10666 views)
Book cover: Network Coding TheoryNetwork Coding Theory
by - Now Publishers Inc
A tutorial on the basics of the theory of network coding. It presents network coding for the transmission from a single source node, and deals with the problem under the more general circumstances when there are multiple source nodes.
(17009 views)
Book cover: Information Theory, Inference, and Learning AlgorithmsInformation Theory, Inference, and Learning Algorithms
by - Cambridge University Press
A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.
(29310 views)