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Information theory
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Information theory
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Academic year 2016/2017
- 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
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Sommario del corso
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Course objectives
The course represents an introduction to classical results of Shannon information theory.
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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.
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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.
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Learning assessment methods
The assesment comprises a written test followed by an oral examination.
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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.Suggested readings and bibliography
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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
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Class schedule
Lessons: dal 20/02/2017 to 26/05/2017
Notes: Class schedule is available at Computer Science Department courses
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Note
This course will be delivered at the Computer Science Department.
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