1.

Record Nr.

UNINA9910818223603321

Autore

Dragotti Pier Luigi

Titolo

Distributed source coding : theory, algorithms, and applications / / Pier Luigi Dragotti, Michael Gastpar

Pubbl/distr/stampa

Amsterdam ; ; Boston : , : Academic Press/Elsevier, , [2009]

©2009

ISBN

1-282-28683-8

9786612286834

0-08-092274-0

Descrizione fisica

1 online resource (359 p.)

Disciplina

621.382/16 22

621.38216

Soggetti

Data compression (Telecommunication)

Multisensor data fusion

Coding theory

Electronic data processing - Distributed processing

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Front Cover; Distributed Source Coding; Copyright Page; Table of Contents; List of Contributors; Introduction; Part I: Theory; Chapter 1. Foundations of Distributed Source Coding; 1.1 Introduction; 1.2 Centralized Source Coding; 1.2.1 Lossless Source Coding; 1.2.2 Lossy Source Coding; 1.2.3 Lossy Source Coding for Sources with Memory; 1.2.4 Some Notes on Practical Considerations; 1.3 Distributed Source Coding; 1.3.1 Lossless Source Coding; 1.3.2 Lossy Source Coding; 1.3.3 Interaction; 1.4 Remote Source Coding; 1.4.1 Centralized; 1.4.2 Distributed: The CEO Problem

1.5 Joint Source-channel CodingAcknowledgments; Appendix A: Formal Definitions and Notations; A.1 Notation; A.1.1 Centralized Source Coding; A.1.2 Distributed Source Coding; A.1.3 Remote Source Coding; References; Chapter 2. Distributed Transform Coding; 2.1 Introduction; 2.2 Foundations of Centralized Transform Coding; 2.2.1 Transform Coding Overview; 2.2.2 Lossless Compression; 2.2.3 Quantizers; 2.2.4 Bit Allocation; 2.2.5 Transforms; 2.2.6 Linear Approximation; 2.3 The



Distributed Karhunen--Loève Transform; 2.3.1 Problem Statement and Notation; 2.3.2 The Two-terminal Scenario

2.3.3 The Multiterminal Scenario and the Distributed KLT Algorithm2.4 Alternative Transforms; 2.4.1 Practical Distributed Transform Coding with Side Information; 2.4.2 High-rate Analysis of Source Coding with Side Informationat Decoder; 2.5 New Approaches to Distributed Compression with FRI; 2.5.1 Background on Sampling of 2D FRI Signals; 2.5.2 Detailed Example: Coding Scheme for Translatinga Bi-level Polygon; 2.6 Conclusions; References; Chapter 3. Quantization for Distributed Source Coding; 3.1 Introduction; 3.2 Formulation of the Problem; 3.2.1 Conventions

3.2.2 Network Distributed Source Coding3.2.3 Cost, Distortion, and Rate Measures; 3.2.4 Optimal Quantizers and Reconstruction Functions; 3.2.5 Example: Quantization of Side Information; 3.3 Optimal Quantizer Design; 3.3.1 Optimality Conditions; 3.3.2 Lloyd Algorithm for Distributed Quantization; 3.4 Experimental Results; 3.5 High-rate Distributed Quantization; 3.5.1 High-rate WZ Quantization of Clean Sources; 3.5.2 High-rate WZ Quantization of Noisy Sources; 3.5.3 High-rate Network Distributed Quantization; 3.6 Experimental Results Revisited; 3.7 Conclusions; References

Chapter 4. Zero-error Distributed Source Coding4.1 Introduction; 4.2 Graph Theoretic Connections; 4.2.1 VLZE Coding and Graphs; 4.2.2 Basic Definitions and Notation; 4.2.3 Graph Entropies; 4.2.4 Graph Capacity; 4.3 Complementary Graph Entropy and VLZE Coding; 4.4 Network Extensions; 4.4.1 Extension 1: VLZE Coding When Side Information May Be Absent; 4.4.2 Extension 2: VLZE Coding with Compound Side Information; 4.5 VLZE Code Design; 4.5.1 Hardness of Optimal Code Design; 4.5.2 Hardness of Coding with Length Constraints; 4.5.3 An Exponential-time Optimal VLZE Code Design Algorithm

4.6 Conclusions

Sommario/riassunto

The advent of wireless sensor technology and ad-hoc networks has made DSC a major field of interest. Edited and written by the leading players in the field, this book presents the latest theory, algorithms and applications, making it the definitive reference on DSC for systems designers and implementers, researchers, and graduate students.This book gives a clear understanding of the performance limits of distributed source coders for specific classes of sources and presents the design and application of practical algorithms for realistic scenarios. Material covered includes the use of