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Cooperative and Graph Signal Processing

Principles and Applications

Specificaties
Paperback, blz. | Engels
Elsevier Science | 2018
ISBN13: 9780128136775
Rubricering
Elsevier Science e druk, 2018 9780128136775
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Samenvatting

Cooperative and Graph Signal Processing: Principles and Applications presents the fundamentals of signal processing over networks and the latest advances in graph signal processing. A range of key concepts are clearly explained, including learning, adaptation, optimization, control, inference and machine learning. Building on the principles of these areas, the book then shows how they are relevant to understanding distributed communication, networking and sensing and social networks. Finally, the book shows how the principles are applied to a range of applications, such as Big data, Media and video, Smart grids, Internet of Things, Wireless health and Neuroscience.

With this book readers will learn the basics of adaptation and learning in networks, the essentials of detection, estimation and filtering, Bayesian inference in networks, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the perspective of flow of information, and how to apply signal processing methods in distributed settings.

Specificaties

ISBN13:9780128136775
Taal:Engels
Bindwijze:Paperback

Inhoudsopgave

<p>PART 1 BASICS OF INFERENCE OVER NETWORKS<br>1. Asynchronous Adaptive Networks<br>2. Estimation and Detection Over Adaptive Networks<br>3. Multitask Learning Over Adaptive Networks With Grouping Strategies<br>4. Bayesian Approach to Collaborative Inference in Networks of Agents<br>5. Multiagent Distributed Optimization<br>6. Distributed Kalman and Particle Filtering<br>7. Game Theoretic Learning</p> <p>PART 2 SIGNAL PROCESSING ON GRAPHS<br>8. Graph Signal Processing<br>9. Sampling and Recovery of Graph Signals<br>10. Bayesian Active Learning on Graphs<br>11. Design of Graph Filters and Filterbanks<br>12. Statistical Graph Signal Processing: Stationarity and Spectral Estimation<br>13. Inference of Graph Topology<br>14. Partially Absorbing Random Walks: A Unified Framework for Learning on Graphs</p> <p>PART 3 DISTRIBUTED COMMUNICATIONS, NETWORKING, AND SENSING<br>15. Methods for Decentralized Signal Processing With Big Data<br>16. The Edge Cloud: A Holistic View of Communication, Computation, and Caching<br>17. Applications of Graph Connectivity to Network Security<br>18. Team Methods for Device Cooperation in Wireless Networks<br>19. Cooperative Data Exchange in Broadcast Networks<br>20. Collaborative Spectrum Sensing in the Presence of Byzantine Attack</p> <p>PART 4 SOCIAL NETWORKS<br>21. Dynamics of Information Diffusion and Social Sensing<br>22. Active Sensing of Social Networks: Network Identification From Low-Rank Data<br>23. Dynamic Social Networks: Search and Data Routing<br>24. Information Diffusion and Rumor Spreading<br>25. Multilayer Social Networks<br>26. Multiagent Systems: Learning, Strategic Behavior, Cooperation, and Network Formation</p> <p>PART 5 APPLICATIONS<br>27. Genomics and Systems Biology<br>28. Diffusion Augmented Complex Extended Kalman Filtering for Adaptive Frequency Estimation in Distributed Power Networks<br>29. Beacons and the City: Smart Internet of Things<br>30. Big Data<br>31. Graph Signal Processing on Neuronal Networks</p>
€ 114,94
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        Cooperative and Graph Signal Processing