Vai al contenuto principale

Department of Mathematics "Giuseppe Peano"

# Laurea Magistrale (M.Sc.) in Stochastics and Data Science

Oggetto:
Oggetto:

Oggetto:

## Information theory

Oggetto:

Course ID
MAT0052
Teaching staff
Prof. Marco Grangetto
Prof. Matteo Sereno
Year
2nd year
Teaching period
Second semester
Type
D.M. 270 TAF C - Related or integrative
Credits/Recognition
6
Course disciplinary sector (SSD)
INF/01 - informatica
Delivery
Class Lecture
Language
English
Attendance
Optional
Type of examination
Written and oral
Oggetto:

Oggetto:

## Course objectives

The course represents an introduction to classical results of Shannon information theory.

Oggetto:

## Results of learning outcomes

At the end of the course the student will have the capacity to apply information theory tools and approaches to both theoretical and practical problems related to information management, coding, representation, protection and information metrics.

Oggetto:

## Course delivery

The course will be based on theretical lessons followed by in class exercises and computer based experiments. Personal training on assigned exercises is important for the success in this class.

Oggetto:

## Learning assessment methods

The assesment comprises a written test followed by an oral examination.

Oggetto:

## Program

The course is structured in two parts.

The first part of the course is devoted to the classical information theory. In particular, the addressed topics are: definition of information and source types, the concept of entropy, source coding, Shannon's first theorem (source coding), uniquely decodable codes, optimality of Huffman coding, models of noisy channels, definition of the channel capacity according to Shannon's theorem (channel coding).

The second part of the course is devoted to the study of source coding and channel coding algorithms used in many applications, communication systems and networks. The selected topics include arithmetic coding, the Lempel-Ziv-Welch algorithms and state of the art standards for image and video compression. As far as channel coding is regarded the course will introduce linear block codes, cyclic codes, convolutional codes and fountain codes.

Oggetto:

R. W. Yeung, "Information Theory and Network Coding,  ISBN: 978-0-387-79233-0

Thomas M. Cover, Joy A. Thomas, "Elements of Information Theory, 2nd Edition", ISBN: 978-0-471-24195-9

Oggetto:

## Class schedule

Lessons: dal 20/02/2017 to 26/05/2017

Notes: Class schedule is available at Computer Science Department courses

Oggetto:

## Note

This course will be delivered at the Computer Science Department.

Oggetto:
Last update: 20/02/2017 10:03