Distributed source coding theory, algorithms, and applications
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 implemen...
| Otros Autores: | , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Amsterdam ; Boston :
Academic Press/Elsevier
[2009]
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| Edición: | 1st ed |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627334306719 |
Tabla de Contenidos:
- 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
