Publication

A source coding scheme using sparse graphs: Modern Coding Theory Course Exam 2008

2008
Student Projects

Abstract

This is the report that submitted towards the final examination evaluation of the doctoral course \textit{Modern Coding theory} by Ruediger Urbanke at EPFL during Spring 2008. The problem studied can be roughly stated as source coding or compression using sparse graphs. We discuss a simple source coding problem and analyze its performance using an analytical tool formulated by \textit{Wormald}, usually employed to describe the expected behaviour of a suitably conditioned stochastic process on graph. A simulation investigation of the chosen scheme is also presented to verify the theoretical analysis.

Official source

https://infoscience.epfl.ch/entities/publication/107625fa-bfe3-4a91-bc33-da93f3c920e0

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2008
Student Projects

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/107625fa-bfe3-4a91-bc33-da93f3c920e0

About this result

Related concepts (32)

Coding theory

Coding theory is the study of the properties of codes and their respective fitness for specific applications. Codes are used for data compression, cryptography, error detection and correction, data transmission and data storage. Codes are studied by various scientific disciplines—such as information theory, electrical engineering, mathematics, linguistics, and computer science—for the purpose of designing efficient and reliable data transmission methods.

Source code

In computing, source code, or simply code, is any collection of text, with or without comments, written using a human-readable programming language, usually as plain text. The source code of a program is specially designed to facilitate the work of computer programmers, who specify the actions to be performed by a computer mostly by writing source code. The source code is often transformed by an assembler or compiler into binary machine code that can be executed by the computer.

Dense graph

In mathematics, a dense graph is a graph in which the number of edges is close to the maximal number of edges (where every pair of vertices is connected by one edge). The opposite, a graph with only a few edges, is a sparse graph. The distinction of what constitutes a dense or sparse graph is ill-defined, and is often represented by 'roughly equal to' statements. Due to this, the way that density is defined often depends on the context of the problem.

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A source coding scheme using sparse graphs: Modern Coding Theory Course Exam 2008

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