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Last updated:

August 6, 2022

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

Badge on Completion

Certificate of completion

Unlimited Duration

Description

This is a graduate-level introduction to mathematics of information theory.

We will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression.

Course Curriculum

    • 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 14: Channel coding Unlimited
    • Chapter 15: Channel coding: Achievability bounds Unlimited
    • Chapter 16: Linear codes. Channel capacity. Unlimited
    • Chapter 17: Channels with input constraints. Gaussian channels. Unlimited
    • Chapter 18: Lattice codes Unlimited
    • Chapter 19: Channel coding: Energy-per-bit, continuous-time channels Unlimited
    • Chapter 20: Advanced channel coding. Source-Channel separation. Unlimited
    • Chapter 21: Channel coding with feedback Unlimited
    • Chapter 22: Capacity-achieving codes via Forney concatenation Unlimited
    • Chapter 23: Rate-distortion theory Unlimited
    • Chapter 24: Rate distortion: Achievability bounds Unlimited
    • Chapter 25: Evaluating R(D). Lossy Source-Channel separation. Unlimited
    • Chapter 26: Multiple-access channel Unlimited
    • Chapter 27: Examples of MACs. Maximal Pe and zero-error capacity. Unlimited
    • Chapter 28: Random number generators Unlimited

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Massachusetts Institute of Technology