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Communication and Information Engineering Department Zewail City of Science and Technology CIE425: Information Theory and Coding Lecturer: Ziad A. ElSahn 
 

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OVERVIEW This course covers fundamentals of information theory and coding, including entropy, average mutual information, channel capacity, block codes and convolutional codes. Topics also include asymptotic equipartition property, entropy rates of a stochastic process, data compression, channel capacity, differential entropy, and the Gaussian channel.  Course File Updated as of February 14, 2017 [PDF] Teaching Load (Spring 2017)  Lectures (2
hours), Tutorials (2 hours)


1 Basics and Fundamentals of Information Theory 
Introduction to Information Theory 2 Source Coding and Data Compression 3 Channel Capacity Theorems 4 Channel Coding Theorems and Algorithms 5 Related Topics and Applications 
Rate Distortion Theory 

 Thomas M. Cover, Joy A. Thomas, Elements of Information Theory,
2nd Edition, John Wiley & Sons, Inc., 2006. Useful Links: 
Claude Shannon, “A mathematical theory of communication,” The Bell System Technical Journal, 1948.
[PDF] 

Lecture 1: Introduction to
Information Theory
[PDF] 

Distribution of a total mark of 100:  MidTerm
Exams (30 marks): 60 minutes, closed book (2 equal weight exams) 

© Copyright 20052017, Ziad A. ElSahn  Last updated: May 16, 2017 