Data Compression: Shannon-Fano Algorithm

This lecture covers the Shannon-Fano algorithm for data compression, exploring concepts such as entropy, lossless compression, and performance analysis. It delves into the principles of representing sequences of letters efficiently, demonstrating how the algorithm assigns bits based on letter probabilities. The lecture also discusses the limitations of compression without loss and introduces the transition from Shannon-Fano to Huffman algorithm. It concludes with insights on compression techniques for images and sound, emphasizing the trade-offs between file size reduction and data fidelity.