Verfügbarkeit: Particle filters for random set models

Particle filters for random set models:

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Bibliographische Detailangaben
1. Verfasser:	Ristic, Branko (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	New York, NY [u.a.] Springer 2013
Schlagworte:	Informatik Ingenieurwissenschaften Künstliche Intelligenz Mathematik Computer science Artificial intelligence Mathematics Engineering Wahrscheinlichkeit BAYES
Online-Zugang:	BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FWS01 UBY01 Volltext Inhaltsverzeichnis Abstract
Beschreibung:	1 Online-Ressource
ISBN:	9781461463160
DOI:	10.1007/978-1-4614-6316-0

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Datensatz im Suchindex

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adam_text	PARTICLE FILTERS FOR RANDOM SET MODELS / RISTIC, BRANKO : 2013 TABLE OF CONTENTS / INHALTSVERZEICHNIS INTRODUCTION REFERENCES BACKGROUND A BRIEF REVIEW OF PARTICLE FILTERS ONLINE SENSOR CONTROL NON-STANDARD MEASUREMENTS IMPRECISE MEASUREMENTS IMPRECISE MEASUREMENT FUNCTION UNCERTAIN IMPLICATION RULES PARTICLE FILTER IMPLEMENTATION APPLICATIONS MULTIPLE OBJECTS AND IMPERFECT DETECTION RANDOM FINITE SETS MULTI-OBJECT STOCHASTIC FILTERING OSPA METRIC SPECIALIZED MULTI-OBJECT FILTERS BERNOULLI FILTER PHD AND CPHD FILTER REFERENCES APPLICATIONS INVOLVING NON-STANDARD MEASUREMENTS ESTIMATION USING IMPRECISE MEASUREMENT MODELS LOCALIZATION USING THE RECEIVED SIGNAL STRENGTH PREDICTION OF AN EPIDEMIC USING SYNDROMIC DATA SUMMARY FUSION OF SPATIALLY REFERRING NATURAL LANGUAGE STATEMENTS LANGUAGE, SPACE AND MODELLING AN ILLUSTRATIVE EXAMPLE CLASSIFICATION USING IMPRECISE LIKELIHOODS MODELLING CLASSIFICATION RESULTS REFERENCES OBJECT PARTICLE FILTERS BERNOULLI PARTICLE FILTERS STANDARD BERNOULLI PARTICLE FILTERS BERNOULLI BOX-PARTICLE FILTER PHD/CPDH PARTICLE FILTERS WITH ADAPTIVE BIRTH INTENSITY EXTENSION OF THE PHD FILTER EXTENSION OF THE CPHD FILTER IMPLEMENTATION A NUMERICAL STUDY STATE ESTIMATION FROM PHD/CPHD PARTICLE FILTERS PARTICLE FILTER APPROXIMATION OF THE EXACT MULTI-OBJECT FILTER REFERENCES SENSOR CONTROL FOR RANDOM SET BASED PARTICLE FILTERS BERNOULLI PARTICLE FILTER WITH SENSOR CONTROL THE REWARD FUNCTION BEARINGS ONLY TRACKING IN CLUTTER WITH OBSERVER CONTROL TARGET TRACKING VIA MULTI-STATIC DOPPLER SHIFTS SENSOR CONTROL FOR PHD/CPHD PARTICLE FILTERS THE REWARD FUNCTION A NUMERICAL STUDY SENSOR CONTROL FOR THE MULTI-TARGET STATE PARTICLE FILTER PARTICLE APPROXIMATION OF THE REWARD FUNCTION A NUMERICAL STUDY REFERENCES MULTI-TARGET TRACKING OSPA-T: A PERFORMANCE METRIC FOR MULTI-TARGET TRACKING THE PROBLEM AND ITS CONCEPTUAL SOLUTION THE BASE DISTANCE AND LABELING OF ESTIMATED TRACKS NUMERICAL EXAMPLES TRACKERS BASED ON RANDOM SET FILTERS MULTI-TARGET TRACKERS BASED ON THE BERNOULLI PF MULTI-TARGET TRACKERS BASED ON THE PHD PARTICLE FILTER ERROR PERFORMANCE COMPARISON USING THE OSPA-T ERROR APPLICATION: PEDESTRIAN TRACKING VIDEO DATASET AND DETECTIONS DESCRIPTION OF ALGORITHMS NUMERICAL RESULTS REFERENCES ADVANCED TOPICS FILTER FOR EXTENDED TARGET TRACKING MATHEMATICAL MODELS EQUATIONS OF THE BERNOULLI FILTER FOR AN EXTENDED TARGET NUMERICAL IMPLEMENTATION SIMULATION RESULTS APPLICATION TO A SURVEILLANCE VIDEO CALIBRATION OF TRACKING SYSTEMS BACKGROUND AND PROBLEM FORMULATION THE PROPOSED CALIBRATION ALGORITHM IMPORTANCE SAMPLING WITH PROGRESSIVE CORRECTION APPLICATION TO SENSOR BIAS ESTIMATION REFERENCES INDEX DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. PARTICLE FILTERS FOR RANDOM SET MODELS / RISTIC, BRANKO : 2013 ABSTRACT / INHALTSTEXT “PARTICLE FILTERS FOR RANDOM SET MODELS” PRESENTS COVERAGE OF STATE ESTIMATION OF STOCHASTIC DYNAMIC SYSTEMS FROM NOISY MEASUREMENTS, SPECIFICALLY SEQUENTIAL BAYESIAN ESTIMATION AND NONLINEAR OR STOCHASTIC FILTERING. THE CLASS OF SOLUTIONS PRESENTED IN THIS BOOK IS BASED ON THE MONTE CARLO STATISTICAL METHOD. THE RESULTING ALGORITHMS, KNOWN AS PARTICLE FILTERS, IN THE LAST DECADE HAVE BECOME ONE OF THE ESSENTIAL TOOLS FOR STOCHASTIC FILTERING, WITH APPLICATIONS RANGING FROM NAVIGATION AND AUTONOMOUS VEHICLES TO BIO-INFORMATICS AND FINANCE. WHILE PARTICLE FILTERS HAVE BEEN AROUND FOR MORE THAN A DECADE, THE RECENT THEORETICAL DEVELOPMENTS OF SEQUENTIAL BAYESIAN ESTIMATION IN THE FRAMEWORK OF RANDOM SET THEORY HAVE PROVIDED NEW OPPORTUNITIES WHICH ARE NOT WIDELY KNOWN AND ARE COVERED IN THIS BOOK. THESE RECENT DEVELOPMENTS HAVE DRAMATICALLY WIDENED THE SCOPE OF APPLICATIONS, FROM SINGLE TO MULTIPLE APPEARING/DISAPPEARING OBJECTS, FROM PRECISE TO IMPRECISE MEASUREMENTS AND MEASUREMENT MODELS. THIS BOOK IS IDEAL FOR GRADUATE STUDENTS, RESEARCHERS, SCIENTISTS AND ENGINEERS INTERESTED IN BAYESIAN ESTIMATION DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
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spellingShingle	Ristic, Branko Particle filters for random set models Informatik Ingenieurwissenschaften Künstliche Intelligenz Mathematik Computer science Artificial intelligence Mathematics Engineering Wahrscheinlichkeit (DE-588)4137007-7 gnd BAYES (DE-588)4245375-6 gnd
subject_GND	(DE-588)4137007-7 (DE-588)4245375-6
title	Particle filters for random set models
title_auth	Particle filters for random set models
title_exact_search	Particle filters for random set models
title_full	Particle filters for random set models Branko Ristic
title_fullStr	Particle filters for random set models Branko Ristic
title_full_unstemmed	Particle filters for random set models Branko Ristic
title_short	Particle filters for random set models
title_sort	particle filters for random set models
topic	Informatik Ingenieurwissenschaften Künstliche Intelligenz Mathematik Computer science Artificial intelligence Mathematics Engineering Wahrscheinlichkeit (DE-588)4137007-7 gnd BAYES (DE-588)4245375-6 gnd
topic_facet	Informatik Ingenieurwissenschaften Künstliche Intelligenz Mathematik Computer science Artificial intelligence Mathematics Engineering Wahrscheinlichkeit BAYES
url	https://doi.org/10.1007/978-1-4614-6316-0 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026021655&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026021655&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
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