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1. |
Record Nr. |
UNINA9910703408803321 |
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Autore |
Bennett George L. |
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Titolo |
Groundwater-quality data in the north San Francisco Bay shallow aquifer study unit, 2012 : results from the California GAMA Program / / by George L. Bennett V and Miranda S. Fram ; prepared in cooperation with the California State Water Resources Control Board |
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Pubbl/distr/stampa |
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Reston, Virginia : , : U.S. Department of the Interior, U.S. Geological Survey, , 2014 |
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Descrizione fisica |
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1 online resource (x, 94 pages) : color illustrations, color maps |
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Collana |
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Soggetti |
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Groundwater - Quality - California - San Francisco Bay |
Water quality management - California - San Francisco Bay Area - Data processing |
Water quality management - California - San Francisco Bay |
Water-supply - California - San Francisco Bay |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from title screen (viewed on Nov. 3, 2014). |
Chiefly tables. |
"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program." |
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Nota di bibliografia |
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Includes bibliographical references (pages 15-20). |
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2. |
Record Nr. |
UNINA9910782886303321 |
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Autore |
Dragotti Pier Luigi |
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Titolo |
Distributed source coding : theory, algorithms, and applications / / Pier Luigi Dragotti, Michael Gastpar |
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Pubbl/distr/stampa |
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Amsterdam ; ; Boston : , : Academic Press/Elsevier, , [2009] |
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©2009 |
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ISBN |
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1-282-28683-8 |
9786612286834 |
0-08-092274-0 |
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Descrizione fisica |
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1 online resource (359 p.) |
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Disciplina |
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Soggetti |
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Data compression (Telecommunication) |
Multisensor data fusion |
Coding theory |
Electronic data processing - Distributed processing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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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 |
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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 |
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Sommario/riassunto |
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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 |
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