EEC 266
— Information Theory & Coding
Topics include Entropy, Relatively Entropy, Mutual Information; Asymptotic Equipartition Property; Entropy Rates of Stochastic Process; Data Compression; Channel Capacity; Differential Entropy; Gaussian Channel; Rate Distortion Theory; Network Information Theory.
Topics
- Entropy
- Relatively Entropy
- Mutual Information
- Asymptotic Equipartition Property
- Entropy Rates of Stochastic Process
- Data Compression
- Channel Capacity
- Differential Entropy
- Gaussian Channel
- Rate Distortion Theory
- Network Information Theory
Topics explicitly listed in official catalogue description
Prerequisites & course information
Course Description: Topics include Entropy, Relatively Entropy, Mutual Information; Asymptotic Equipartition Property; Entropy Rates of Stochastic Process; Data Compression; Channel Capacity; Differential Entropy; Gaussian Channel; Rate Distortion Theory; Network Information Theory. Learning Activities: Lecture 3 hour(s), Project. Grade Mode: Letter. Learning Activities: Lecture 3 hour(s), Project. Grade Mode: Letter.
Sources
- Course catalogue ↗2026-2027