Lecture

Data Compression and Shannon's Theorem: Performance Analysis

Description

This lecture explains Shannon's theorem, stating that the compression of a source cannot go below its entropy. It also discusses the performance of Shannon Fano codes, showing they are close to the theoretical optimum. The relationship between entropy and the average number of questions in a Shannon Fano code is explored, providing insights into the exact definition of entropy.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.