Data Compression and Shannon's Theorem: Shannon-Fano Coding

This lecture covers the Shannon-Fano coding method, which aims to represent sequences with the fewest bits per letter. By analyzing letter frequencies and minimizing differences between left and right partitions, the algorithm constructs efficient codes. The lecture demonstrates the step-by-step process of creating Shannon-Fano codes and compares them to Huffman codes. It also explores the concept of entropy and how it relates to the efficiency of the coding process. Through examples and calculations, students learn how to apply Shannon-Fano coding to achieve optimal data compression. The lecture concludes by discussing the implications of lossy compression methods in data storage and transmission.