Multi-Sensor Filtering Fusion with Censored Data Under a Constrained Network Environment
eBook - ePub

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

  1. 262 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

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

About this book

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.

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Yes, you can access Multi-Sensor Filtering Fusion with Censored Data Under a Constrained Network Environment by Hang Geng,Zidong Wang,Yuhua Cheng in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title
  4. Copyright
  5. Dedication
  6. Contents
  7. List of Figures
  8. List of Tables
  9. List of Symbols
  10. Preface
  11. Acknowledgement
  12. Foreword
  13. List of Contributors
  14. 1 Introduction
  15. 2 Optimal Filtering for Networked Systems with Channel Fading and Measurement Censoring
  16. 3 Tobit Kalman Filter with Time-Correlated Multiplicative Sensor Noises under Redundant Channel Transmission
  17. 4 State Estimation under Non-Gaussian Lévy and Time-Correlated Additive Sensor Noises: A Modified Tobit Kalman Filtering Approach
  18. 5 Protocol-Based Filter Design under Integral Measurements and Probabilistic Sensor Failures: The Censored Data Case
  19. 6 Distributed Optimal Filtering Fusion over a Packet-Delaying Network Subject to Censored Data: A Probabilistic Perspective
  20. 7 Federated Tobit Kalman Filtering Fusion with Dead-Zone-Like Censoring and Dynamical Bias under the Round-Robin Protocol
  21. 8 Multi-Sensor Filtering Fusion with Parametric Uncertainties and Measurement Censoring: Monotonicity and Boundedness
  22. 9 Protocol-Based Fusion Estimator Design for State-Saturated Systems with Dead-Zone-Like Censoring under Deception Attacks
  23. 10 Variance-Constrained Filtering Fusion for Nonlinear Cyber-Physical Systems with the Denial-of-Service Attacks and Stochastic Communication Protocol
  24. 11 Conclusions and Future Topics
  25. Bibliography
  26. Index