Multi-Sensor Filtering Fusion with Censored Data Under a Constrained Network Environment
- Indbinding:
- Hardback
- Udgivet:
- 26. august 2024
- Størrelse:
- 156x234x16 mm.
- Vægt:
- 544 g.
- 2-3 uger.
- 19. december 2024
På lager
Forlænget returret til d. 31. januar 2025
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Multi-Sensor Filtering Fusion with Censored Data Under a Constrained Network Environment
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.
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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