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Mathematics of Data Fusion - Hung T. Nguyen
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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. weltbild.at > Bücher > Wissenschaft & Technik > Fachbücher Technik, [PU: Kluwer Academic Publishers]

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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. weltbild.at > Bücher > Wissenschaft & Technik > Fachbücher Technik, [PU: Kluwer Academic Publishers]

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Mathematics of Data Fusion (Theory and Decision Library B) - Goodman, I.R.; Mahler, R.P.; Nguyen, Hung T.
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Mathematics of Data Fusion (Theory and Decision Library B) - Goodman, I.R., Mahler, R.P., Hung T. Ngu
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Details zum Buch
Mathematics of Data Fusion
Autor:

Goodman, I. R.; Hung T. Nguyen; Mahler, R. P.

Titel:

Mathematics of Data Fusion

ISBN-Nummer:

9780792346746

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.

Detailangaben zum Buch - Mathematics of Data Fusion


EAN (ISBN-13): 9780792346746
ISBN (ISBN-10): 0792346742
Gebundene Ausgabe
Erscheinungsjahr: 1997
Herausgeber: Springer-Verlag GmbH
524 Seiten
Gewicht: 0,941 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 21.03.2007 12:18:22
Buch zuletzt gefunden am 15.12.2016 06:12:04
ISBN/EAN: 9780792346746

ISBN - alternative Schreibweisen:
0-7923-4674-2, 978-0-7923-4674-6

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