Data Compression: Theory and Applications
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Course Description
The course focuses on the theory and algorithms underlying modern data compression. The first part of the course introduces techniques for entropy coding and for lossless compression. The second part covers lossy compression including techniques for multimedia compression. The last part of the course will cover advanced theoretical topics and applications, such as neural network based compression, distributed compression, and computation over compressed data. Prerequisites: basic probability and programming background (EE178, CS106B or equivalent), a course in signals and systems (EE102A), or instructor's permission.
Grading Basis
ROP - Letter or Credit/No Credit
Min
3
Max
3
Course Repeatable for Degree Credit?
No
Course Component
Lecture
Enrollment Optional?
No
Programs
EE274
is a
completion requirement
for:
- (from the following course set: )
- (from the following course set: )