ECE 7620

Fundamentals of Data Compression

Course Description

Course information provided by the Courses of Study 2024-2025.

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.

When Offered Spring.

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

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

• 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.

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