Information Theory

Recommended Prerequisites

Mathematical Analysis I, Statistics, Introduction to Programming and Problem Solving, Principles of Procedural Programming

Learning Outcomes

To provide the students with the main concepts and foundations of information theory and its applications in computational learning, source and channel coding and cryptography. The goal is to expose the algebraic foundations in order to enable the student to learn the abstract concepts of information theory and the sophisticated mathematics of coding.

The course will contribute to the acquisition of the following competences:

Instrumental:

• Analysis and synthesis of complex problems;
• Mathematical Reasoning;
• Abstraction and generalization;
• Problem solving, namely in the area of computational learning, data compression channel coding and cryptography.

Personal:

• Team work;
• Critical reasoning.

Systematic:

• Self-learning

Research.

Work Placement(s)

No

Head Lecturer(s)

Paulo Fernando Pereira de Carvalho

Assessment Methods

Assessment
Exam: 100.0%

Bibliography

K. Sayood, Introduction to data compression: second edition, Morgan Kaufman, 2000. (selected chapters)

J. C. MacKay (2003) Information Theory, Inference and Learning Algorithms, University of Cambridge, (http://www.inference.phy.cam.ac.uk/mackay/itila/book.html)(selected chapters)

W. Trappe, L. Washington, Introduction to Cryptography with Coding Theory, Prentice Hall, 2^nd Edition (selected chapters)

Shu Lin, Daniel J. Costello (2004) Error Control Coding, Second Edition, Prentice Hall; 2nd Edition (selected chapters)

Carvalho, P. (2011) – Slides de Teoria de Informação, DEI-FCTUC.

 

Complementar/Complementary:

T. Cover, J. Thomas (1991) Elements of Information Theory, John Wiley&Sons.