Networked Multisensor Decision and Estimation Fusion: Based on Advanced Mathematical Methods

Author:   Yunmin Zhu (Sichuan University, China) ,  Jie Zhou ,  Xiaojing Shen ,  Enbin Song
Publisher:   Taylor & Francis Inc
ISBN:  

9781439874523


Pages:   440
Publication Date:   05 July 2012
Format:   Hardback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Networked Multisensor Decision and Estimation Fusion: Based on Advanced Mathematical Methods


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Overview

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.

Full Product Details

Author:   Yunmin Zhu (Sichuan University, China) ,  Jie Zhou ,  Xiaojing Shen ,  Enbin Song
Publisher:   Taylor & Francis Inc
Imprint:   CRC Press Inc
Dimensions:   Width: 15.60cm , Height: 2.80cm , Length: 23.40cm
Weight:   0.748kg
ISBN:  

9781439874523


ISBN 10:   1439874522
Pages:   440
Publication Date:   05 July 2012
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Introduction. Parallel Statistical Binary Decision Fusion. General Network Statistical Decision Fusion. Some Uncertain Decision Combination. Convex Linear Estimation Fusion. Kalman Filtering Fusion. Robust Estimation Fusion. References.

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Yunmin Zhu, Jie Zhou

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