Advanced Information Theory: Random Binning

Related lectures (27)

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Explores channel coding with a focus on convolutional codes, emphasizing error detection, correction, and decoding processes.

Covers entropy, source coding, encoding maps, decodability, prefix-free codes, and Kraft-McMillan's inequality.

Covers source coding theorems, entropy, and various source models in information theory.

Explores geodesic convexity in metric spaces and its applications, discussing properties and the stability of inequalities.

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

Discusses conditional entropy and its role in data compression techniques.

Explores the Rockafellar Theorem in optimal transport, focusing on c-cyclical monotonicity and convex functions.

Explores channel coding, BICM, and LLRs in wireless communication systems, emphasizing the importance of error detection and correction.

Discusses conditional entropy and its role in information theory and data compression.

Explores correlations of the Liouville function along deterministic and independent sequences, covering key concepts and theorems.