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Table of contents (16 chapters)
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Front Matter
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Introduction
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Introduction to Data Fusion
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Front Matter
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The Random Set Approach to Data Fusion
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Front Matter
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Use of Conditional and Relational Events in Data Fusion
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Front Matter
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About this book
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.
Authors and Affiliations
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NCCOSC RDTE DIV, San Diego, USA
I. R. Goodman
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Lockheed Martin Tactical Defences Systems, Saint Paul, USA
Ronald P. S. Mahler
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Department of Mathematical Sciences, New Mexico State University, Las Cruces, USA
Hung T. Nguyen
Bibliographic Information
Book Title: Mathematics of Data Fusion
Authors: I. R. Goodman, Ronald P. S. Mahler, Hung T. Nguyen
Series Title: Theory and Decision Library B
DOI: https://doi.org/10.1007/978-94-015-8929-1
Publisher: Springer Dordrecht
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media B.V. 1997
Hardcover ISBN: 978-0-7923-4674-6Published: 31 August 1997
Softcover ISBN: 978-90-481-4887-5Published: 07 December 2010
eBook ISBN: 978-94-015-8929-1Published: 14 March 2013
Edition Number: 1
Number of Pages: XII, 508
Topics: Applications of Mathematics, Artificial Intelligence, Statistics, general