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Introduction to Bayesian Tracking and Particle Filters: Studies in Big Data, cartea 126

Autor Lawrence D. Stone, Roy L. Streit, Stephen L. Anderson
en Limba Engleză Paperback – 2 iun 2024
This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking. It also introduces the reader to multiple target tracking by presenting useful approximate methods that are easy to implement compared to full-blown multiple target trackers.
The book presents the basic concepts of Bayesian inference and demonstrates the power of the Bayesian method through numerous applications of particle filters to tracking and smoothing problems. It emphasizes target motion models that incorporate knowledge about the target’s behavior in a natural fashion rather than assumptions made for mathematical convenience.
The background provided by this book allows a person to quickly become a productive member of a project team using Bayesian filtering and to develop new methods and techniques for problems the team may face.

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Specificații

ISBN-13: 9783031322440
ISBN-10: 3031322444
Pagini: 118
Ilustrații: VI, 118 p. 58 illus., 53 illus. in color.
Dimensiuni: 155 x 235 mm
Ediția:2023
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Big Data

Locul publicării:Cham, Switzerland

Cuprins

Introduction.- Bayesian Single Target Tracking.- Bayesian Particle Filtering.- Simple Multiple Target Tracking.- Intensity Filters.

Textul de pe ultima copertă

This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking. It also introduces the reader to multiple target tracking by presenting useful approximate methods that are easy to implement compared to full-blown multiple target trackers.
The book presents the basic concepts of Bayesian inference and demonstrates the power of the Bayesian method through numerous applications of particle filters to tracking and smoothing problems. It emphasizes target motion models that incorporate knowledge about the target’s behavior in a natural fashion rather than assumptions made for mathematical convenience.
The background provided by this book allows a person to quickly become a productive member of a project team using Bayesian filtering and to develop new methods and techniques for problems the team may face.


Caracteristici

Provides a quick and insightful introduction to Bayesian Particle Filtering Requires only basic knowledge of probability and statistics Illustrates and motivates cardinal concepts with practical examples and minimal mathematical complexity