Catalog Description: Entropy rates of information sources, fundamental limits of data compression, Huffman and arithmetic codes; mutual information, fundamental limits of information transmission over noisy communication channels with/without feedback. Selected topics in information storage, lossy data compression, and network information theory.

Prerequisite: ECEN 3810, Introduction to Probability

Textbook:

Elements of Information Theory

Reference:

Information Theory and Reliable Communications

Goals:

To provide an in-depth understanding of various information theoretic limits, including entropy, reciprocity and rate distortion function, and to discuss various applications of information theory.

Topics:

Single-user information theory: noiseless source coding; channel coding; noisy source coding (quantization and rate distortion theory); and source-channel coding theorem (separation theorem).
Multi-user information theory: noiseless source coding; channel coding.
Hypothesis testing.
Large deviation theory.

Computer Usage:

A few assignments require use of computer.

Laboratory Projects:

None.

ABET Category Content:

Engineering Science: 2 credits or 67%

Engineering Design: 1 credit or 33%