Cooperative and Graph Signal Processing,
Edition 1 Principles and Applications
Edited by Petar Djuric and Cédric Richard

Publication Date: 20 Jun 2018

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.

Key Features

  • Presents the first book on cooperative signal processing and graph signal processing
  • Provides a range of applications and application areas that are thoroughly covered
  • Includes an editor in chief and associate editor from the IEEE Transactions on Signal Processing and Information Processing over Networks who have recruited top contributors for the book
About the author
Edited by Petar Djuric, Stony Brook University, Stony Brook, NY, USA and Cédric Richard, Université Nice Sophia Antipolis, Nice, France
Book details
ISBN: 9780128136775
Page Count: 866
Retail Price : £84.99
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Researchers and graduate students in signal and information processing over networks