Instructor: Shashi Prabh
Email: shashi.prabh@snu
Office: D036E
Office hour: Wednesdays 3:30 - 5 PM, or by appointment
Lectures: 3:30 - 5:00 PM Tuesdays and Thursdays
Location: D022
Probability theory is a prerequisite for this course. Since such a course has not been offered to CS students, this prerequisite will be taught in the course. However students must be be able to grasp the prerequisite sufficiently quickly. The course is suited for students who are not averse to mathematics. Students intending to register for the course are expected to meet the instructor beforehand to determine whether they can handle the course material.
Relevant probability theory basics. Concept of information, entropy, entropy rate, source coding, data compression algorithms, noisy channel coding, channel capacity, Gaussian channels, multiple access channels, broadcast channels and Kolmogorov complexity.
Thomas M. Cover, Joy A. Thomas. Elements of Information Theory, 2nd Edition, Wiley 2006. ISBN: 978-0-471-24195-9
Assignments: 20%
Project: 20%
Mid-term exam: 25%
Final exam: 35%