Cooperative and Graph Signal Processing: Principles and Applications

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商品描述

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.

  • 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

商品描述(中文翻譯)

《合作與圖形信號處理:原理與應用》介紹了網絡信號處理的基礎知識以及圖形信號處理的最新進展。書中清晰解釋了一系列關鍵概念,包括學習、適應、優化、控制、推理和機器學習。在這些領域的基礎上,本書展示了它們如何與分散通信、網絡和感知以及社交網絡相關。最後,本書展示了這些原則如何應用於各種應用領域,如大數據、媒體和視頻、智能電網、物聯網、無線健康和神經科學。

通過閱讀本書,讀者將學習網絡中的適應和學習的基礎知識,檢測、估計和過濾的基本要素,網絡中的貝葉斯推理,優化和控制,機器學習,圖形信號處理,分散通信中的信號處理,從信息流的角度看社交網絡,以及如何在分散環境中應用信號處理方法。

本書是第一本關於合作信號處理和圖形信號處理的專書,涵蓋了多個應用和應用領域。書中的主編和副編來自IEEE信號處理和網絡信息處理交易期刊,他們邀請了頂尖的專家為本書作出貢獻。