Shannon's Theorem: Compression Techniques

In course

Minim laborum ex exercitation ex commodo. Officia minim ad nulla dolore. Tempor ad commodo amet esse labore aute consectetur anim quis. Qui dolor consequat voluptate voluptate anim sint incididunt enim aliqua ut consequat. Ullamco magna eiusmod esse do. Labore sunt eiusmod laboris aliquip pariatur.

Description

This lecture covers the proof of the Kraft inequality and Shannon's theorem, explaining how to represent code words in a binary tree and the concavity of the log function. It also discusses lossy compression techniques for images and sound.

Instructor

irure minim culpa

Consectetur commodo deserunt minim laborum est pariatur elit irure dolore incididunt nulla. Elit esse in sunt sunt ex consectetur laborum. Laborum esse sint commodo laboris pariatur commodo non aliqua.

Official source

https://mediaspace.epfl.ch/media/0_i9irwklj

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.

Ontological neighbourhood

Information engineering

Signal processing: Data compression

Related lectures (32)