Multi-Sensor Filtering Fusion with Censored Data under a Constrained Network Environment

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Multi-Sensor Filtering Fusion with Censored Data under a Constrained Network Environment

Geng, Hang/ Wang, Zidong/ Cheng, Yuhua

ウェブストア価格 ¥33,566（本体¥30,515）
CRC Press（2024/08発売）
外貨定価 US$ 160.00
ポイント 305pt

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製本 Hardcover:ハードカバー版／ページ数 238 p.
言語 ENG
商品コード 9781032555508
DDC分類 629.892637

Full Description

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.

1.Introduction 2. Optimal Filtering for Networked Systems with Channel Fading and Measurement Censoring 3. Tobit Kalman Filter with Time-Correlated Multiplicative Sensor Noise Under Redundant Channel Transmission 4. State Estimation Under Non-Gaussian Lévy and Time-Correlated Additive Sensor Noise 5. Protocol-Based Filter Design Under Integral Measurement and Probabilistic Sensor Failure 6. Distributed Filtering Fusion over Packet-Delaying Networks Subject to Censored Data 7. Federated Filtering Fusion with Dead-Zone-Like Censoring and Dynamical Bias Under Round-Robin Protocol 8. Multi-Sensor Filtering Fusion with Parametric Uncertainty and Measurement Censoring 9. Protocol-Based Filtering Fusion for State-Saturated Systems with Dead-Zone-Like Censoring Under Deception Attacks 10. Variance-Constrained Filtering Fusion for Nonlinear Cyber-Physical Systems Under Stochastic Communication Protocol 11. Conclusion and Furture Topics