Information and Coding Theory
Explore information measures; compression and channels; error correction. Concepts and connections are available independently of video coverage.
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Mutual information measures statistical dependence as the reduction in uncertainty from observing another variable.
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Conditional entropy averages remaining uncertainty after another variable is observed.
KL divergence compares distributions and is generally asymmetric, with support conditions affecting finiteness.
Capacity bounds achievable reliable information rates for a specified channel model.
Minimum distance d permits correcting up to floor((d-1)/2) arbitrary symbol errors.
Hamming distance counts differing positions between equal-length strings.
Explore information measures; compression and channels; error correction. Concepts and connections are available independently of video coverage.