The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking―without information loss―into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book.
"Sinopsis" puede pertenecer a otra edición de este libro.
The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking―without information loss―into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
Condición: new. Questo è un articolo print on demand. Nº de ref. del artículo: bf8e3084ebb04c588ecf23994af44ed6
Cantidad disponible: Más de 20 disponibles
Librería: StainesBookhub, Weybridge, SURRE, Reino Unido
Condición: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage. Nº de ref. del artículo: SPRINGERNEW50146
Cantidad disponible: 1 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9783030611903
Cantidad disponible: Más de 20 disponibles
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware - The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking-without information loss-into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book. 240 pp. Englisch. Nº de ref. del artículo: 9783030611903
Cantidad disponible: 2 disponibles
Librería: moluna, Greven, Alemania
Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents an accessible guide to AC and GF written for engineers to address engineering problemsProvides theory in an easy to understand manner and application of the theory to real life projects and solutionsDescribes GFs and their applicat. Nº de ref. del artículo: 448685746
Cantidad disponible: Más de 20 disponibles
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In English. Nº de ref. del artículo: ria9783030611903_new
Cantidad disponible: Más de 20 disponibles
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Hardback. Condición: New. 2021 ed. ?The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking-without information loss-into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book. Nº de ref. del artículo: LU-9783030611903
Cantidad disponible: Más de 20 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking-without information loss-into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book. Nº de ref. del artículo: 9783030611903
Cantidad disponible: 1 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking-without information loss-into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 240 pp. Englisch. Nº de ref. del artículo: 9783030611903
Cantidad disponible: 1 disponibles
Librería: Books Puddle, Woodside, NY, Estados Unidos de America
Condición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP. Nº de ref. del artículo: 26390048490
Cantidad disponible: 4 disponibles