Information Theory and Coding

Related lectures (30)

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Covers the basics of information theory and its applications in various fields.

Explores the Source Coding Theorem, entropy, Huffman coding, and conditioning's impact on entropy reduction.

Covers the application of entropy in algorithms, focusing on sorting and decision-making strategies.

Discusses conditional entropy and its role in data compression techniques.

Covers source coding, typical sequences, stationarity, and efficient encoding in information theory.

Explores random walks, Moran model, bacterial chemotaxis, entropy, information theory, and coevolving sites in proteins.

Covers information measures like entropy, joint entropy, and mutual information in information theory and data processing.

Covers data compression techniques, including source coding and unique decodability concepts.

Covers concepts of entropy, Gaussian distributions, and channel capacity with constraints.

Explores encoding and decoding techniques in communication systems, focusing on fundamental limits and mutual information computations.