3 ECTS credits
75 h study time
Offer 1 with catalog number 4021175FNR for all students in the 1st semester at a (F) Master - specialised level.
The course aims to introduce the information theory based on the approaches of Shannon on the one hand and Kinchine on the other. Concepts of auto-information, entropy, conditional entropies, ambiguity, transinformation and redundancy are introduced and many practical examples are treated and computed. The channel capacity of a channel is estimated and applied to practical examples; e.g. DSL on twisted pair telephony cables and for wireless radio channels. The fundamental coding theorems of Shannon are discussed. Codes met unequal code lengths are developed and optimised.
Additional material:
Richard E. Blahut, Principles and Practice of Information Theory
In this course Information Theory is introduced and treated as a part of Signal Theory and the study of communication channels. It is an introductory course, and hence the focus is laid on the description of the physical properties which are required to model a communication channel.
The main goal of the course, however, is to be able to apply the theory. For the latter the course can be regarded as specialisation in communication theory.
This course contributes to the general competences of a Master in Computer Science.
The student will be able to compute the entropy of information sources and the capacity of communication channels. He/she will also be able to propose optimal coding schemes, in some practical cases of importance for the binary encoding of discrete sources.
The final grade is composed based on the following categories:
Oral Exam determines 100% of the final mark.
Within the Oral Exam category, the following assignments need to be completed:
Oral examination (closed book type). Questioning is partly theoretical and partly practical; e.g. the development of a code, the computation of entropy, channel capacity, redundancy etc. in a practical case.
This offer is part of the following study plans:
Master of Applied Sciences and Engineering: Computer Science: Artificial Intelligence
Master of Applied Sciences and Engineering: Computer Science: Multimedia
Master of Applied Sciences and Engineering: Computer Science: Software Languages and Software Engineering
Master of Applied Sciences and Engineering: Computer Science: Multimedia for Northwestern Polytechnical University (NPU)
Master of Applied Sciences and Engineering: Computer Science: Data Management and Analytics