Universal Information Processing
Lecture
Main Campus
Course Description
Universal schemes for information processing tasks such as compression, communication, sequential probability assignments, prediction, denoising, and filtering. Characterization of performance limits in stochastic, semi-stochastic, and individual sequence settings. Ziv-Lempel compression as an end goal, and as an engine for other information processing tasks. Trade Offs between performance (e.g. accuracy), amounts of data processed, and computation.
EE 376C
Units: 3
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Typically Offered
Not Available
Grading Basis
Letter or Credit/No Credit
Class Level
Graduate
Instructional Mode
In Person
Gen Ed Requirement(s)
None
