20 - Session 20/ClipID:39853 previous clip next clip

Keywords: coding Information entropy Bayesian Inference Mutual Information Information Theory Shannon's Theorems Channel Capacity Message Passing Sum-Product Algorithm Source Coding Channel Coding

Recording date 2022-01-10

Course

Information Theory and Coding [Winter 2021-2022]

Lecturer

Ali Bereyhi

Via

IdM-login

Language

English

Organisational Unit

Friedrich-Alexander-Universität Erlangen-Nürnberg

Producer

Friedrich-Alexander-Universität Erlangen-Nürnberg

Format

lecture

Context

On demand

Type

university lecture

This is the recording of Session 20, given on Monday, Jan 10, 2022. In this session, we learn the Gaussian channel. To calculate its capacity, we study the concept of differential entropy and learn how to deal with continuous random variables in information theory. This session is partially consistent with Chapter 11.

Up next

21 - Session 21
Schloss1
Ali Bereyhi
2022-01-14
IdM-login
22 - Session 22 (Tutorial 6)
Schloss1
Ali Bereyhi
2022-01-17
IdM-login

More clips in this category "Friedrich-Alexander-Universität Erlangen-Nürnberg"

Strom- und Spannungsmessung
2022-01-19
IdM-login
protected  
Einführung in die Numerik - Wiederholung 17.01.22
2022-01-19
IdM-login / Passwort
protected  
Exercise 1
2022-01-19
IdM-login
protected  
Exercise 2
2022-01-19
IdM-login
protected  
Einführung in die Numerik - Vorlesung 19.01.22
2022-01-19
Passwort
protected  
Exercise 4
2022-01-19
IdM-login
protected