| Description |
1 online resource (xxvi, 856 pages) : illustrations |
| Series |
Artech House information warfare library |
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Artech House information warfare library.
|
| Contents |
Statistical Multisource-MultitargetInformation Fusion; Contents; Preface xxiii; Acknowledgments xxv; Chapter 1 Introduction to the Book; Part I Unified Single-Target Multisource Integration; Chapter 2 Si ngle-Target Filtering 25; Chapter 3 General Data Modeling 89; Chapter 4 Random Set Uncertainty Representations 119; Chapter 5 UGA Measurements 157; Chapter 6AGA Measurements 211; Chapter 7AGU Measurements 249; Chapter 8 Generalized State-Estimates 271; Chapter 9 Finite-Set Measurement 287; Part II Uni ed Multitarget-MultisourceIntegration 305; Chapter 10 Conventional Multitarget Filtering 307 |
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Chapter 11 Multitarget Calculus 343Chapter 12 Multitarget Likelihood Functions 399; Chapter 13 Multitarget Markov Densities 461; Chapter 14 The Multitarget Bayes Filter 483; Part III Approximate Multitarget Filtering 539; Chapter 15 Multitarget Particle Approximation 541; Chapter 16 Multitarget-Moment Approximation 565; Chapter 17 Multi-Bernoulli Approximation 655; Appendix A Glossary of Notation 683; Appendix BDirac Delta Functions 693; Appendix CGradient Derivatives 695; Appendix DFundamental Gaussian Identity 699; Appendix E Finite Point Processes 705 |
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Appendix FFISST and Probability Theory 711F.1 MULTIOBJECT PROBABILITY THEORY 711; Appendix G Mathematical Proofs 717; Appendix HSolutions to Exercises 777; References 821; Index 839 |
| Summary |
This comprehensive resource provides you with an in-depth understanding of finite-set statistics (FISST)? a recently developed method which unifies much of information fusion under a single probabilistic, in fact Bayesian, paradigm. The book helps you master FISST concepts, techniques, and algorithms, so you can use FISST to address real-world challenges in the field. You learn how to model, fuse, and process highly disparate information sources, and detect and track non-cooperative individual/platform groups and conventional non-cooperative targets |
| Bibliography |
Includes bibliographical references (pages 821-836) and index |
| Notes |
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212 MiAaHDL |
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Print version record |
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digitized 2010 HathiTrust Digital Library committed to preserve pda MiAaHDL |
| Subject |
Multisensor data fusion -- Mathematics
|
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Expert systems (Computer science)
|
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Bayesian statistical decision theory.
|
|
Automatic tracking.
|
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Signal processing.
|
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Tracking radar.
|
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Target acquisition.
|
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Expert Systems
|
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COMPUTERS -- Expert Systems.
|
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Automatic tracking
|
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Bayesian statistical decision theory
|
|
Expert systems (Computer science)
|
|
Multisensor data fusion -- Mathematics
|
|
Signal processing
|
|
Target acquisition
|
|
Tracking radar
|
|
Multisensor data fusion -- Mathematics.
|
|
Expert systems (Computer science)
|
|
Bayesian statistical decision theory.
|
|
Automatic tracking.
|
|
Signal processing.
|
|
Tracking radar.
|
|
Target acquisition.
|
|
Matematisk statistik -- databehandling.
|
| Form |
Electronic book
|
| LC no. |
2007274985 |
| ISBN |
1596930926 |
|
9781596930926 |
|
1596930934 |
|
9781596930933 |
|
