MIT OpenCourseWare
Information Theory
Art: Palmer, Edward, 1803-1872, Figures 113-123. Plate Electrical Machines, 1840 · Public domain
- Instructor
- Prof. Yury Polyanskiy
- Term
- Spring 2016
- Level
- Graduate
- What's inside
- 11 problem sets · 1 exam · 1 lecture note · 30 other files · 3 web pages
- Materials open
- MIT OCW
Other versions of this course
- 6.441 · Spring 2016 · Study here (this version)
- 6.441 · Spring 2010 · Study here
About this course
Source: MIT OpenCourseWare 6.441 Information Theory, Spring 2016, Prof. Yury Polyanskiy — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: none is claimed; materials are grouped by MIT's own sections. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.
Materials are grouped the way MIT organized them. A verified, course-wide order has not been established here.
Before you start
Prerequisites are not listed here. Check MIT's own syllabus for this course.
How this course was organized
What's here, and what isn't
- No lecture or session order could be confirmed for this course.
Not included here
3 items from the source could not be safely included:
- MIT's page format for this item wasn't recognized clearly enough to place it safely. (3 items)
Materials by section
Grouped by section, as MIT organized them. Not sequenced or ordered.
Lecture Notes
29 files
- 6.441S16: Chapter 1: Information Measures: Entropy and Divergence Download
- 6.441S16: Chapter 2: Information Masures: Mutual Information Download
- 6.441S16: Chapter 3: Sufficient Statistic. Continuity of Divergence and Mutual Information. Download
- 6.441S16: Chapter 4: Extremization of Mutual Information: Capacity Saddle Point Download
- 6.441S16: Chapter 5: Single-Letterization. Probability of Error. Entropy Rate. Download
- 6.441S16: Chapter 6: Variable-Length Lossless Compression Download
- 6.441S16: Chapter 7: Fixed-length (almost lossless) compression. Slepian-Wolf problem. Download
- 6.441S16: Chapter 8: Compressing Stationary Ergodic Sources Download
- 6.441S16: Chapter 9: Universal Compression Download
- 6.441S16: Chapter 10: Binary Hypothesis Testing Download
- 6.441S16: Chapter 11: Hypothesis Testing Asymptotics I Download
- 6.441S16: Chapter 12: Information Projection and Large Deviation Download
- 6.441S16: Chapter 13: Hypothesis Testing Asymptotics II Download
- 6.441S16: Chapter 14: Channel Coding Download
- 6.441S16: Chapter 15: Channel Coding: Achievability Bounds Download
- 6.441S16: Chapter 16: Linear Codes. Channel Capacity Download
- 6.441S16: Chapter 17: Channels with Input Constraints. Gaussian Channels. Download
- 6.441S16: Chapter 18: Lattice Codes (by O. Ordentlich) Download
- 6.441S16: Chapter 19: Channel Coding: Energy-Per-Bit, Continuous-Time Channels Download
- 6.441S16: Chapter 20: Advanced Channel Coding. Source-Channel Separation. Download
- 6.441S16: Chapter 21: Channel Coding with Feedback Download
- 6.441S16: Chapter 22: Capacity-Achieving Codes Via Forney Concatenation Download
- 6.441S16: Chapter 23: Rate-Distortion Theory Download
- 6.441S16: Chapter 24: Rate Distortion: Achievability Bounds Download
- 6.441S16: Chapter 25: Evaluating R(D). Lossy Source-Channel Separation. Download
- 6.441S16: Chapter 26: Multiple-Access Channel Download
- 6.441S16: Chapter 27: Examples of MACs. Maximal Pe and zero-Error Capacity. Download
- 6.441S16: Chapter 28: Random Number Generators Download
- 6.441S16: Course Notes Download
Assignments
11 problem sets
- 6.441S16: Problem Set 1 Download
- 6.441S16: Problem Set 2 Download
- 6.441S16: Problem Set 3 Download
- 6.441S16: Problem Set 4 Download
- 6.441S16: Problem Set 5 Download
- 6.441S16: Problem Set 6 Download
- 6.441S16: Problem Set 7 Download
- 6.441S16: Problem Set 8 Download
- 6.441S16: Problem Set 9 Download
- 6.441S16: Problem Set 10 Download
- 6.441S16: Problem Set 11 Download
Exams
MIT OpenCourseWare, Prof. Yury Polyanskiy, 6.441 Information Theory, Spring 2016.
License: CC BY-NC-SA 4.0 · Edition: Spring 2016 · Open the original course on OCW ↗
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