Lectures related to Shannon-Fano Codes

Covers the Source Coding Theorem, source models, entropy, regular sources, and examples.

Explores Shannon-Fano coding for efficient data compression and its comparison to Huffman coding.

Discusses linear codes' dimension and Hamming weight with examples and theorems.

Explores the Hamming Code for error correction, emphasizing its ability to correct single-bit errors.

Discusses conditional entropy and its role in data compression techniques.

Explores the replica method in determining the expectation of log z as small n approaches zero, showcasing mathematical challenges and solutions.

Covers Convolutional Codes, Viterbi Algorithm, state and branch metric computations, and survivor path length limitations.