Home » Course Layouts » Free Course Layout Udemy
This is a graduate-level introduction to mathematics of information theory.
0
1
English
English [CC]
FREE
- Learn basic syntax that can apply to any language.
- Learn what is a programming language and the basic concepts for beginners.
- Understand what is Javascript in it's truest form.
- Know the basic syntax of Javascript.
- Know some hidden quirks in Javascript.
Description
We will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression.
Course content
-
- Chapter 1: Information measures: Entropy and divergence Unlimited
- Chapter 2: Information measures: Mutual information Unlimited
- Chapter 3: Sufficient statistic. Continuity of divergence and mutual information. Unlimited
- Chapter 4: Extremization of mutual information: Capacity saddle point Unlimited
- Chapter 5: Single-letterization. Probability of error. Entropy rate. Unlimited
-
- Chapter 6: Variable-length Lossless Compression Unlimited
- Chapter 7: Fixed-length (almost lossless) compression. Slepian-Wolf problem Unlimited
- Chapter 8: Compressing stationary ergodic sources Unlimited
- Chapter 9: Universal compression Unlimited
- Chapter 10: Binary hypothesis testing Unlimited
- Chapter 11: Hypothesis testing asymptotics I Unlimited
- Chapter 12: Information projection and Large deviation Unlimited
- Chapter 13: Hypothesis testing asymptotics II Unlimited
- Chapter 23: Rate-distortion theory Unlimited
- Chapter 24: Rate distortion: Achievability bounds Unlimited
- Chapter 25: Evaluating R(D). Lossy Source-Channel separation. Unlimited
Instructor
Massachusetts Institute of Technology
5
5
1
1916
1520
