random sets theory and applications by ronald p s mahler

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Random Sets

Author : John Goutsias
ISBN : 9781461219422
Genre : Mathematics
File Size : 21. 70 MB
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This IMA Volume in Mathematics and its Applications RANDOM SETS: THEORY AND APPLICATIONS is based on the proceedings of a very successful 1996 three-day Summer Program on "Application and Theory of Random Sets." We would like to thank the scientific organizers: John Goutsias (Johns Hopkins University), Ronald P.S. Mahler (Lockheed Martin), and Hung T. Nguyen (New Mexico State University) for their excellent work as organizers of the meeting and for editing the proceedings. We also take this opportunity to thank the Army Research Office (ARO), the Office ofNaval Research (0NR), and the Eagan, MinnesotaEngineering Center ofLockheed Martin Tactical Defense Systems, whose financial support made the summer program possible. Avner Friedman Robert Gulliver v PREFACE "Later generations will regard set theory as a disease from which one has recovered. " - Henri Poincare Random set theory was independently conceived by D.G. Kendall and G. Matheron in connection with stochastic geometry. It was however G.

Signal Processing Sensor Fusion And Target Recognition

Author : Ivan Kadar
ISBN : UOM:39015048109840
Genre : Optical pattern recognition
File Size : 84. 60 MB
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Annual Meeting Of The North American Fuzzy Information Processing Society Nafips

Author : Jim Keller
ISBN : 0780374614
Genre : Soft computing
File Size : 51. 41 MB
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Statistical Multisource Multitarget Information Fusion

Author : Ronald P. S. Mahler
ISBN : 1596930926
Genre : Technology & Engineering
File Size : 56. 83 MB
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This comprehensive resource provides practitioners with an in-depth understanding of finite-set statistics (FISST)--a recently developed method that has been gaining much attention among professionals because it unifies information fusion, utilizing statistics that most engineers learn as undergraduates.

Mathematics Of Data Fusion

Author : I.R. Goodman
ISBN : 0792346742
Genre : Mathematics
File Size : 90. 41 MB
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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.

Information Theory Analysis For Data Fusion

Author :
ISBN : OCLC:227871494
Genre :
File Size : 60. 9 MB
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Complete theoretical development of random set unified data fusion, and place under theoretically solid information theory foundation suitable for publication. Findings: (1) Showed that optimal sensor allocation (redirection of the reallocatable sensors in a sensor suite) can be subsumed within the random set approach to information fusion, via generalization of nonlinear optimal control theory. (2) Showed that random set theory and information theory provides a common basis for performance evaluation in information fusion. Showed that parameters (e.g. target I.D. performance) can be measured in terms of information, and likewise for user defined constraints (e.g. subjective or multiple definitions of information). (3) Showed that both precise and ambiguous observations can be fused by generalizing Bayesian measurement models and the standard Bayesian recursive nonlinear filtering equations. (4) Seven chapters were completed and submitted for a book published in 1997 by Kluwer. (5) Organized a joint ONR/ARO scientific workshop on Applications and Theory of Random Sets.

Automatic Object Recognition

Author : Firooz A. Sadjadi
ISBN : 0819415383
Genre : Image processing
File Size : 41. 12 MB
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