Information Theory (EE 654)

2021 Spring
Faculty of Engineering and Natural Sciences
Electronics Engineering(EE)
3
10.00
Özgür Erçetin oercetin@sabanciuniv.edu,
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English
Doctoral, Master
--
Formal lecture
Interactive,Project based learning,Task based learning
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CONTENT

Entropy and mutual information concepts, Markov chains and entropy rate. Shannon?s lossless source coding, channel capacity, white and colored Gaussian channels, rate distortion theory with applications to scalar and vector quantizer design. Multi-user information theory and applications.

OBJECTIVE

Developing a strong abstract thinking to study limits of the communications and signal processing.
Understanding the fundamentals of compression applications such as Zip, JPEG, MPEG, etc., as well as the meaning of transmission capacity of channels, and the ways to achieve the capacity.

LEARNING OUTCOME

Building a mathematical model of concrete concepts.
Understanding the limits of compression and transmission
Analyze and design compression and error correction control algorithms

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Final 50
Participation 10
Individual Project 40

RECOMENDED or REQUIRED READINGS

Textbook

Cover, Thomas, Elements of Information Theory