EE4560 Information theory

Topics: Source and channel coding
This course explains the basic ideas of information theory and the correspondences between the elements of this theory and certain natural concepts of importance in a wide number of fields, such as transmission, storage, authoring and protection of data. On the basis of simple concepts from probabiliby calculus, models are developed for a discrete information source and a discrete communication channel. Further, the theoretical basics for developing source coding algorithms is provided, as well as the basics of optimal data transmission through a discrete communication channel. The following topics will be covered:
  • (Differential) Entropy, Relative Entropy and Mutual Information
  • Asymptotic Equipartition Property
  • Data Compression
  • Channel Capacity
  • Gaussian Channel
  • Rate-Distortion Theory
  • Network Information Theory

Upon completion of this course the student will understand the fundamentals of Information Theory, which includes the following: (a) the correspondences between the elements of this theory and certain natural concepts of importance in a wide number of fields, such as transmission, storage, authoring and protection of data, (b) core theorems of information theory, (c) the models that are developed for a discrete information source and a discrete communication channel on the basis of simple concepts from probability calculus, (d) how to develop source coding algorithms, and (e) how to secure optimal data transmission through a (noisy) discrete communication channel.

Teachers

dr.ir. Jos Weber

Network coding, channel coding, cyber security

dr. Jorge Martinez

Acoustic signal processing

Last modified: 2019-12-16

Details

Credits: 5 EC
Period: 0/0/4/0
Contact: Jorge Martinez