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HU Credits:
3
Degree/Cycle:
2nd degree (Master)
Responsible Department:
Computer Sciences
Semester:
2nd Semester
Teaching Languages:
English and Hebrew
Campus:
E. Safra
Course/Module Coordinator:
Yuval Kochman
Coordinator Office Hours:
by appointment
Teaching Staff:
Prof Yuval Kochman
Course/Module description:
A basic course in Information Theory: compression, communication, and the role of information measures in statistical inference.
Course/Module aims:
Knowledge of basic terms in Information theory, main theorems, and most importantly: how to approach and analyze informational settings.
Learning outcomes - On successful completion of this module, students should be able to:
Formulate an information-related setting using appropriate terms. Understand what are the relevant informational quantities. Be able to solve simple problems.
Attendance requirements(%):
none
Teaching arrangement and method of instruction:
Frontal.
Course/Module Content:
1. Review of topics from the basic class, with extensions such as continuous distributions.
2. Lossy source coding and joint source-channel coding.
3. Statistical inference: Bounds on hypothesis testing, estimation and learning using information-theoretic quantities.
4. Introduction to multi-terminal information theory: side information and multi-terminal problems.
5. Time permitting, extensions: Polar codes, linear codes and lattices, secrecy and more.
Required Reading:
Cover and Thomas: Elements of Information Theory (relevant chapters)
Additional Reading Material:
Gallager: Information theory and reliable communication
Polyanskiy and Wu: Lecture notes on information theory
Shannon: A Mathematical Theory of Communication
Grading Scheme :
Essay / Project / Final Assignment / Referat 50 %
Submission assignments during the semester: Exercises / Essays / Audits / Reports / Forum / Simulation / others 25 %
Mid-terms exams 25 %
Additional information:
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