Entropy, relative entropy and mutual information, asymptotic equipartition property, entropy rate of a stochastic process, data compression, gambling, channel capacity, differential entropy, Gaussian channel, rate distortion theory, information theory and statistics, maximum entropy, universal source coding, Kolmogorov complexity, network information theory, application of information theory on portfolio theory, inequalities in information theory.
- Teacher: Μιλτιάδης Αναγνώστου
Description : The course covers key concepts and areas in information theory, including entropy, data compression, channel capacity, and their applications in various fields like gambling, statistics, and portfolio theory. It also addresses topics such as Gaussian channels, rate distortion theory, Kolmogorov complexity, and network information theory.
Credits/ECTS : 4
Program it belongs to : MS level course of the integrated Master Program of ECE School NTUA
Course Type: Compulsory or Selective : Selective
Course Type: Core or Specialization : Specialization
StudyLoad : 3 theory; 9 homestudy
Evaluation method : Written exam 100%, homework exercises bonus 15%
Distribution of teaching and learning materials : Lecture Hours: 39, Homework hours: 16, Study: 65
Audience : students only
Language : el