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Cooperative and graph signal processing : principles and applications

Contributor(s): Material type: TextTextPublication details: London : Academic Press, ©2018.Description: xxviii, 837 p. : ill. (b&w) ; 23.5 cm (Paperback)ISBN:
  • 9780128136775
Subject(s): Additional physical formats: ebook version :: No titleDDC classification:
  • 621.382 23 DJU / B
Summary: "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."-- Provided by publisher.
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Item type Current library Collection Call number Status Date due Barcode
Book Book IIT - Dharwad Electronics, Communications Engineering 621.382 DJU / B (Browse shelf(Opens below)) Available 4698

Includes bibliographical references and index.

"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."-- Provided by publisher.

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