Cooperative and graph signal processing : principles and applications

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Material type: Text

9780128136775

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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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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	IIT - Dharwad	Electronics, Communications Engineering	621.382 DJU / B (Browse shelf(Opens below))	Available		4698

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Previous	621.382 BLA / B Communication acoustics	621.382 BOJ / B Linear algebra for signal processing	621.382 DEL / B Discrete-time processing of speech signals	621.382 DJU / B Cooperative and graph signal processing :	621.382 ELA / B Sparse and redundant representations :	621.382 GAL / B Principles of digital communication	621.382 GAL / B Principles of digital communication	Next

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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