Mathematics of Data Fusion

  • I. R. Goodman
  • Ronald P. S. Mahler
  • Hung T. Nguyen

Part of the Theory and Decision Library book series (TDLB, volume 37)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Introduction

    1. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 1-14
  3. Introduction to Data Fusion

    1. Front Matter
      Pages 15-16
    2. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 17-89
  4. The Random Set Approach to Data Fusion

    1. Front Matter
      Pages 91-91
    2. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 93-129
    3. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 131-173
    4. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 175-218
    5. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 219-262
    6. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 263-293
    7. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 295-338
  5. Use of Conditional and Relational Events in Data Fusion

    1. Front Matter
      Pages 339-344
    2. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 345-358
    3. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 359-367
    4. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 369-382
    5. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 383-403
    6. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 425-454
    7. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 455-480
    8. I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
      Pages 481-501

About this book

Introduction

Data fusion or information fusion are names which have been primarily assigned to military-oriented problems. In military applications, typical data fusion problems are: multisensor, multitarget detection, object identification, tracking, threat assessment, mission assessment and mission planning, among many others. However, it is clear that the basic underlying concepts underlying such fusion procedures can often be used in nonmilitary applications as well. The purpose of this book is twofold: First, to point out present gaps in the way data fusion problems are conceptually treated. Second, to address this issue by exhibiting mathematical tools which treat combination of evidence in the presence of uncertainty in a more systematic and comprehensive way. These techniques are based essentially on two novel ideas relating to probability theory: the newly developed fields of random set theory and conditional and relational event algebra.
This volume is intended to be both an update on research progress on data fusion and an introduction to potentially powerful new techniques: fuzzy logic, random set theory, and conditional and relational event algebra.
Audience: This volume can be used as a reference book for researchers and practitioners in data fusion or expert systems theory, or for graduate students as text for a research seminar or graduate level course.

Keywords

Algebra calculus expert system fuzzy fuzzy logic mathematics natural language set theory statistics systems theory uncertainty

Authors and affiliations

  • I. R. Goodman
    • 1
  • Ronald P. S. Mahler
    • 2
  • Hung T. Nguyen
    • 3
  1. 1.NCCOSC RDTE DIVSan DiegoUSA
  2. 2.Lockheed Martin Tactical Defences SystemsSaint PaulUSA
  3. 3.Department of Mathematical SciencesNew Mexico State UniversityLas CrucesUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-015-8929-1
  • Copyright Information Springer Science+Business Media B.V. 1997
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-4887-5
  • Online ISBN 978-94-015-8929-1
  • About this book
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