《Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning》是一本聚焦智慧型感測器網路跨學科整合的技術專著，ISBN為9781138199743。該書旨在填補機器學習與信號處理視角下智慧型感測器網路系統性研究的學術空白，基於獲獎作者團隊的研究成果構建理論框架。
全書分為機器學習、信號處理與網路協定三部分，分別涵蓋智慧型感測器架構、感測器網路性能最佳化及節能路由協定設計等內容，涉及壓縮感知與採樣、分散式信號處理等核心技術。書中列舉了目標追蹤、結構健康監測等典型套用場景，並通過時空關聯驗證範式提升數據清洗效率，同時以卡爾曼濾波器為例說明水利感測器網路攻擊檢測的實現方案。
基本介紹
- 外文名：Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning
- ISBN：9781138199743
基本信息,內容簡介,圖書目錄,作者簡介,
基本信息
《Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning》的ISBN為9781138199743。
內容簡介
《Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning》聚焦智慧型感測器網路的跨學科整合。本書關注通過機器學習實現感測、網路和智慧型信號處理的緊密集成。
圖書目錄
本書共分為三個部分：機器學習、信號處理與網路協定。機器學習部分描述了機器學習與其他人工智慧原理在感測器網路智慧型中的套用，涵蓋智慧型感測器/換能器架構及數據表示。信號處理部分基於數位訊號處理技術考慮感測器網路性能最佳化，包括路由與特定套用信號處理的跨層集成，以及智慧型交通系統中無線多媒體感測器網路的板載圖像處理。網路協定部分專注於網路協定設計以實現智慧型感測器組網，涵蓋感測器網路的能量高效機會路由協定與多智慧型體驅動的無線感測器協作。
作者簡介
該書基於作者團隊的研究成果構建理論框架。書中呈現了感測領域研究者的研究成果。
內容簡介
Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of se...(展開全部) Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning. Presenting recent research results of world-renowned sensing experts, the book is organized into three parts: Machine Learning-describes the application of machine learning and other AI principles in sensor network intelligence-covering smart sensor/transducer architecture and data representation for intelligent sensors Signal Processing-considers the optimization of sensor network performance based on digital signal processing techniques-including cross-layer integration of routing and application-specific signal processing as well as on-board image processing in wireless multimedia sensor networks for intelligent transportation systems Networking-focuses on network protocol design in order to achieve an intelligent sensor networking-covering energy-efficient opportunistic routing protocols for sensor networking and multi-agent-driven wireless sensor cooperation Maintaining a focus on "intelligent" designs, the book details signal processing principles in sensor networks. It elaborates on critical platforms for intelligent sensor networks and illustrates key applications-including target tracking, object identification, and structural health monitoring. It also includes a paradigm for validating the extent of spatiotemporal associations among data sources to enhance data cleaning in sensor networks, a sensor stream reduction application, and also considers the use of Kalman filters for attack detection in a water system sensor network that consists of water level sensors and velocity sensors.
