ECE 7620

Fundamentals of Data Compression

Course Description

Course information provided by the 2024-2025 Catalog.

Fundamental limits and practical algorithms for data compression. Entropy and other information measures. Variable and fixed-length lossless and lossy source codes. Universal compression. Single-source and network configurations. Applications to text, multimedia compression, and machine learning. This course is intended for Ph.D. students. M.Eng. students should enroll in ECE 5620.

Prerequisites/Corequisites Prerequisite: ECE 4110 and basic Python programming skills.

Outcomes

• Demonstrate use of information measures including entropy, mutual information, relatively entropy, and their properties.
• Compute theoretical limits to compression for both lossless and lossy problems.
• Analyze the performance of lossless and lossy compression schemes, including comparing their performance against the theoretical limits.
• Design lossless and lossy compression algorithms for provided datasets that approach the theoretical limits.

When Offered Spring.

Comments This course is intended for Ph.D. students. M.Eng. students should enroll in ECE 5620.

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