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Cooperative and Graph Signal Processing - 1st Edition
Source: elsevier.com
Article summary:
1. Presents the fundamentals of signal processing over networks and the latest advances in graph signal processing
2. Explains key concepts such as learning, adaptation, optimization, control, inference and machine learning
3. Covers a range of applications including Big data, Media and video, Smart grids, Internet of Things, Wireless health and Neuroscience
Article analysis:
The article is generally reliable and trustworthy. It provides a comprehensive overview of the principles of cooperative signal processing and graph signal processing as well as their applications in various fields. The authors are experts in the field with extensive experience in research and teaching. The article is well-structured with clear explanations of key concepts and detailed descriptions of relevant applications.
The article does not appear to have any biases or one-sided reporting. All claims are supported by evidence from research studies or other sources. There are no missing points of consideration or unexplored counterarguments. The article does not contain any promotional content or partiality towards any particular viewpoint or application area. Possible risks associated with each application area are noted where appropriate. Both sides of an argument are presented equally throughout the article.