Information Theory

Catalog description

This course is a graduate-level introduction to information theory. Information theory is probably the most elegant mathematical theories, with the most direct and significant engineering impacts to our life in the information age. Information theory has found its applications in many areas, including statistics, computer sciences, biology, economics, etc. The focus of this course will be on the direct application of information theory in digital communications. We believe that the most important part of learning information theory is to learn a new way of thinking about engineering problems. In this sense, this course is beneficial not only to communication majored students, but also to students in other engineering disciplines. Prerequisites: a basic course in probability/statistics. Typically offered Fall Spring Summer. Course Learning Outcomes 1. The students will be able to define what is meant by information. 2. The students will be able to show how we can compress the information in a source to its theoretically minimum value and show the tradeoff between data compression and distortion. 3. The students will be able to prove the Channel Coding Theorem and derive the information capacity of different channels. View Class Schedule