Multi-Sensor Filtering Fusion with Censored Data Under a Constrained Network Environment (Paperback)

Language: English

Published by Taylor & Francis Ltd, London, 2026

1032610255 / 9781032610252

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Paperback. This book presents the up-to-date research developments and novel methodologies on multi-sensor filtering fusion (MSFF) for a class of complex systems subject to censored data under a constrained network environment. The contents of this book are divided into two parts covering centralized and distributed MSFF design methodologies. The work provides a framework of optimal centralized/distributed filter design and stability and performance analysis for the considered systems along with designed filters. Simulations presented in this book are implemented using MATLAB.Features:Includes concepts, backgrounds and models on censored data, filtering fusion and communication constraints.Reviews case studies to provide clear engineering insights into the developed fusion theories and techniques.Provides theoretic values and engineering insights of the censored data and constrained network.Discusses performance evaluation of the presented multi-sensor fusion algorithms.Explores promising research directions on future multi-sensor fusion.This book is aimed at graduate students and researchers in networked control, sensor networks, and data fusion. This book presents the up-to-date research developments and novel methodologies on Multi-sensor filtering fusion (MSFF) for a class of complex systems subject to censored data under a constrained network environment. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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Title
Multi-Sensor Filtering Fusion with Censored Data Under a Constrained Network Environment (Paperback)
Author
Hang Geng
Publisher
Taylor & Francis Ltd, London
Publication year
2026
Condition
new
Binding
Paperback
Language
English
ISBN 10
1032610255
ISBN 13
9781032610252

CitiRetail

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AbeBooks seller since June 29, 2022

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