Lecture

Information Theory: Source Coding

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

In course

COM-404: Information theory and coding

The mathematical principles of communication that govern the compression and transmission of data and the design of efficient methods of doing so. ...

Description

This lecture covers the concept of source coding in information theory, focusing on the properties of typical sequences, the notion of stationarity, and the asymptotic equipartition property. Emre Telatar explains the importance of binary representation and the process of encoding information efficiently.

Instructor

Emre Telatar

I. Emre Telatar received the B.Sc. degree in electrical engineering from the Middle East Technical University, Ankara, Turkey, in 1986. He received the S.M. and Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, in 1988 and 1992 respectively. In 1992, he joined the Communications Analysis Research Department at AT&T Bell Laboratories (later Lucent Technologies), Murray Hill, NJ. He has been at the EPFL since 2000. Emre Telatar was the recipient of the IEEE Information Theory Society Paper Award in 2001. He was a program co-chair for the IEEE International Symposium on Information Theory in 2002, and associate editor for Shannon Theory for the IEEE Information Theory Transactions from 2001 to 2004. He was awarded the EPFL Agepoly teaching prize in 2005. Emre Telatar's research interests are in communication and information theories.

Official source

Related concepts (31)

Typical set

In information theory, the typical set is a set of sequences whose probability is close to two raised to the negative power of the entropy of their source distribution. That this set has total probability close to one is a consequence of the asymptotic equipartition property (AEP) which is a kind of law of large numbers. The notion of typicality is only concerned with the probability of a sequence and not the actual sequence itself.

Space–time block code

Space–time block coding is a technique used in wireless communications to transmit multiple copies of a data stream across a number of antennas and to exploit the various received versions of the data to improve the reliability of data transfer. The fact that the transmitted signal must traverse a potentially difficult environment with scattering, reflection, refraction and so on and may then be further corrupted by thermal noise in the receiver means that some of the received copies of the data may be closer to the original signal than others.

Asymptotic equipartition property

In information theory, the asymptotic equipartition property (AEP) is a general property of the output samples of a stochastic source. It is fundamental to the concept of typical set used in theories of data compression. Roughly speaking, the theorem states that although there are many series of results that may be produced by a random process, the one actually produced is most probably from a loosely defined set of outcomes that all have approximately the same chance of being the one actually realized.

Shannon's source coding theorem

In information theory, Shannon's source coding theorem (or noiseless coding theorem) establishes the limits to possible data compression, and the operational meaning of the Shannon entropy. Named after Claude Shannon, the source coding theorem shows that (in the limit, as the length of a stream of independent and identically-distributed random variable (i.i.d.) data tends to infinity) it is impossible to compress the data such that the code rate (average number of bits per symbol) is less than the Shannon entropy of the source, without it being virtually certain that information will be lost.

United Nations

The United Nations, referred to informally as the UN, is an intergovernmental organization whose stated purposes are to maintain international peace and security, develop friendly relations among nations, achieve international cooperation, and serve as a centre for harmonizing the actions of nations. It is the world's largest international organization. The UN is headquartered in New York City (in the United States, but with certain extraterritorial privileges), and the organization has other offices in Geneva, Nairobi, Vienna, and The Hague, where the International Court of Justice is headquartered.

Related lectures (64)

Source Coding and Prefix-Free Codes

Covers source coding, injective codes, prefix-free codes, and Kraft's inequality.

Information Theory and Coding

Covers source coding, Kraft's inequality, mutual information, Huffman procedure, and properties of tropical sequences.

Lecture: Shannon

Covers the basics of information theory, focusing on Shannon's setting and channel transmission.

Information Theory and Coding: Source Coding

Covers source coding, encoder design, and error probability analysis in information theory and coding.

Random Coding: Achievability and Proof Variants