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Intelligente Sensornetzwerke: Die Integration von Sensornetzwerken, Signalprozessen
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Intelligente Sensornetzwerke: Die Integration von Sensornetzwerken, Signalprozessen
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Intelligente Sensornetzwerke: Die Integration von Sensornetzwerken, Signalprozessen-

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Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processi
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    ISBN-13
    9781138199743
    Book Title
    Intelligent Sensor Networks
    ISBN
    9781138199743

    Über dieses Produkt

    Product Identifiers

    Publisher
    Taylor & Francis Group
    ISBN-10
    1138199745
    ISBN-13
    9781138199743
    eBay Product ID (ePID)
    14038445843

    Product Key Features

    Number of Pages
    674 Pages
    Publication Name
    Intelligent Sensor Networks : The Integration of Sensor Networks, Signal Processing and Machine Learning
    Language
    English
    Publication Year
    2016
    Subject
    Signals & Signal Processing, Networking / General, Environmental / General, Electrical, Information Technology
    Type
    Textbook
    Subject Area
    Computers, Technology & Engineering
    Author
    Qi Hao
    Format
    Trade Paperback

    Dimensions

    Item Weight
    16 Oz
    Item Length
    10 in
    Item Width
    7 in

    Additional Product Features

    Intended Audience
    Scholarly & Professional
    Dewey Edition
    23
    Illustrated
    Yes
    Dewey Decimal
    681.20285631
    Table Of Content
    BASICS. Significance of Intelligent Sensor Networks. Elements of Intelligent Sensor Networks. Recent Advances and Applications. SENSING AND SAMPLING. Sensors for Multi-format Signals. Sampling Principle and Architecture. Bio-inspired Sensing. Compressive Sensing (CS) Principle. CS Signal Recovery. Hardware and Software Design for Compressive Sensing. DISTRIBUTED SIGNAL PROCESSING. Sensing Signal Features. Sensing Signal Processing. Networked Processing. Distributed Estimation. Distributed Prediction. INTELLIGENT SIGNAL LEARNING. Machine Learning Basics. Supervise Sensor Signal Learning. Unsupervised Sensor Signal Learning. Variational Bayes for Sensor Signal Learning. Information Geometry for Intelligent Sensor Networking.
    Synopsis
    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., 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., 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., In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts.
    LC Classification Number
    TK7872.D48

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