Data Fusion Mathematics
eBook - ePub

Data Fusion Mathematics

Theory and Practice

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

Data Fusion Mathematics

Theory and Practice

About this book

Data Fusion Mathematics: Theory and Practice offers a comprehensive overview of data fusion (DF) and provides a proper and adequate understanding of the basic mathematics directly related to DF.

This new edition offers updated chapters alongside four new chapters that are based on recent research carried out by the authors, including topics on machine learning techniques, target localization using a network of 2D ground radar, thermal imaging sensors for multi?target angle?only tracking, and multi?sensor data fusion for a single platform and team platforms. This book also covers major mathematical expressions, formulae and equations, and, where feasible, their derivations. It discusses signed distance function concepts, DF models and architectures, aspects and methods of types 1 and 2 fuzzy logics, and related practical applications. In addition, the authors cover soft computing paradigms that are finding increasing applications in multi-sensory DF approaches and applications.

This text is geared toward researchers, scientists, teachers, and practicing engineers interested in and working in the multi?sensor data fusion area.

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Yes, you can access Data Fusion Mathematics by Jitendra R. Raol,S. Sethu Selvi,Sudesh K. Kashyap,Ailneni Sanketh in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Applied Mathematics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Table of Contents
  7. Preface
  8. Acknowledgments
  9. Authors
  10. Introduction
  11. Chapter 1 Introduction to Data Fusion Process
  12. Chapter 2 Statistics, Probability Models, and Reliability: Towards Probabilistic Data Fusion
  13. Chapter 3 Fuzzy Logic and Possibility Theory Based Fusion
  14. Chapter 4 Filtering, Target-Tracking, and Kinematic Data Fusion
  15. Chapter 5 Decentralized Data Fusion Systems
  16. Chapter 6 Component Analysis and Data Fusion
  17. Chapter 7 Image Algebra and Image Fusion
  18. Chapter 8 Decision Theory and Fusion
  19. Chapter 9 Wireless Sensor Networks and Multimodal Data Fusion
  20. Chapter 10 Soft Computing Approaches to Data Fusion
  21. Chapter 11 Machine Learning in Data Fusion
  22. Chapter 12 Target Localization Using Network of 2D Ground Radars
  23. Chapter 13 Multi-Target Angle Only Tracking Using Thermal Imaging Sensors
  24. Chapter 14 Multi-Sensor Data Fusion for Single Platform and Team of Platforms
  25. Appendix A: Some More Algorithms
  26. Appendix B: More Methods of DF and Performance Evaluation Metrics
  27. Appendix C: Automatic Data Fusion
  28. Appendix D: Information on Data Fusion Software Tools
  29. Appendix E: Definitions of Sensor Data Fusion
  30. Appendix F: Some Research Topics in Data Fusion
  31. Index