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Coding and Information Theory

Course Description: Basic definitions, including: information, entropy for zero-memory or memoryless sources. Variable-length coding, including: Huffman code, Shannon-Fano code, and coding efficiency. Markovian (memory) information sources. Rate distortion theory. Channel coding and channel capacity. Error detection and correction codes.
Credit hours: 3
Prerequisites: EE 322
Objectives of the course :

Introduce the student to the concept of source entropy and minimum code length.
Enable the student to create effective variable-length coding for both memoryless and memory sources.
Student introduction to the concept of the maximum channel information rate and channel capacity.
Enable the student to create effective debugging and error-correction codes.

Course outputs :

* Defining the fundamentals and theoretical and mathematical concepts of information theory, source entropy, and coding.
* Definition of different types of error detection and error correction techniques.
Analysis of different types of error detection and error correction techniques.
Review and evaluation of different types of error detection and error correction techniques.

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  • Last updated: 2026-05-20

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