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Autor(en): 
  • Zhu Yunmin
  • Zhou Jie
  • Shen Xiaojing
  • Song Enbin
  • Luo Yingting
  • Networked Multisensor Decision and Estimation Fusion: Based on Advanced Mathematical Methods 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juli 2012  
    Genre:  Schulbücher 
     
    advanced multisensor fusion techniques / Combination Rule / convex optimization algorithms / Convex Optimization Problem / Dempster Shafer Evidences / Dempster Shafer Theory / Dempster’s Rule / distributed sensor systems
    ISBN:  9781439874523 
    EAN-Code: 
    9781439874523 
    Verlag:  Taylor and Francis 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 234 mm / B 156 mm / D 30 mm 
    Gewicht:  748 gr 
    Seiten:  440 
    Illustration:  schwarz-weiss Illustrationen, Tabellen, schwarz-weiss 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    Due to the increased capability, reliability, robustness, and survivability of systems with multiple distributed sensors, multi-source information fusion has become a crucial technique in a growing number of areas-including sensor networks, space technology, air traffic control, military engineering, agriculture and environmental engineering, and industrial control. Networked Multisensor Decision and Estimation Fusion: Based on Advanced Mathematical Methods presents advanced mathematical descriptions and methods to help readers achieve more thorough results under more general conditions than what has been possible with previous results in the existing literature.

    Examining emerging real-world problems, this book summarizes recent research developments in problems with unideal and uncertain frameworks. It presents essential mathematical descriptions and methods for multisensory decision and estimation fusion. Deriving thorough results under general conditions, this reference book:

    • Corrects several popular but incorrect results in this area with thorough mathematical ideas
    • Provides advanced mathematical methods, which lead to more general and significant results
    • Presents updated systematic developments in both multisensor decision and estimation fusion, which cannot be seen in other existing books
    • Includes numerous computer experiments that support every theoretical result

    The book applies recently developed convex optimization theory and high efficient algorithms in estimation fusion, which opens a very attractive research subject on minimizing Euclidean error estimation for uncertain dynamic systems. Supplying powerful and advanced mathematical treatment of the fundamental problems, it will help to greatly broaden prospective applications of such developments in practice.

      



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