Lectures related to Noisy-channel coding theorem

Summarizes Shannon's theorem, emphasizing the importance of entropy in data compression.

Introduces information theory basics, including entropy, independence, and binary entropy function.

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

Explores the construction of signals in space for satellite positioning systems, including navigation data, channel coding, and spreading modulation.

Explores Huffman coding, demonstrating its optimality in average codeword length and prefix-free property.