Mathematics of Data Fusion

By: I.R. Goodman, R.P. Mahler, Hung T. Nguyen

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Hardcover | 31 August 1997

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524 Pages

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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.

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Expert Systems & Knowledge-Based Systems Mathematics Applied Mathematics Probability & Statistics Engineering & Technology Technology in General Maths for Engineers Mathematical Foundation

Set Theory

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Published: 7th December 2010

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Preface
Introduction	p. 1
Data Fusion and Standard Techniques	p. 17
Foundations of Random Sets	p. 93
Finite Random Sets	p. 131
Finite-Set Statistics	p. 175
Fusion of Unambiguous Observations	p. 219
Fusion of Ambiguous Observations	p. 263
Output Measurement	p. 295
Introduction to the Conditional and Relational Event Algebra Aspects of Data Fusion	p. 345
Potential Application of Conditional Event Algebra to Combining Conditional Information	p. 359
Three Particular Conditional Event Algebras	p. 369
Further Development of Product Space Conditional Event Algebra	p. 383
Product Space Conditional Event Algebra as a Tool for Further Analysis of Conditional Event Algebra Issues	p. 405
Testing of Hypotheses for Distinctness of Events and Event Similarity Issues	p. 425
Testing Hypotheses And Estimation Relative To Natural Language Descriptions	p. 455
Development of Relational Event Algebra Proper to Address Data Fusion Problems	p. 481
Index	p. 503
Table of Contents provided by Blackwell. All Rights Reserved.

Mathematics of Data Fusion

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

Other Editions and Formats

Paperback

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