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.ir. Richard Heusdens

Audio and acoustic signal processing, distributed signal processing, information theory (source coding), speech enhancement

Last modified: 2016-04-27

Details

Credits: 5 EC
Period: 0/0/4/0
Contact: Richard Heusdens