Felix govaers (31 resultados)

Condición: New.

Hardback. Condición: New. With the rise of digitalization, AI and modern data communication, engineering is increasingly challenged by the complexity of systems-of-systems, in which perception sensors have their own processing mechanism, information is merged at some centric entity, and cross-platform exchange of data is conceptualized in a holistic approach. Therefore, distributed architectures for data fusion, state estimation, and multi target tracking have been becoming increasingly important. The use of multiple sensors to perceive and compute the situational awareness picture leads to the generation of vast amounts of data, which need to be filtered, enriched, interpreted, and evaluated. This becomes infeasible without the notion of distributed algorithms. Theory and Methods for Distributed Data Fusion Applications first covers the fundamentals of stochastic motion, which constitutes the underlying models in target tracking and parameter estimation. The next chapter exposes the most important basic target tracking and state estimation algorithms and in the next those methods are extended to the estimation of full trajectories with states from multiple time stamps. Then the book introduces the problem of distributed fusion and presents first solutions to it. Then the final 3 chapters cover track fusion methods with unknown cross covariances, the Distributed Kalman Filter and its variants and finally methods for track-to-track association. This book is designed to provide state-of-the-art approaches and algorithms to the interested engineer for data fusion in distributed systems providing a profound understanding of the constraints, assumptions, benefits, and drawbacks. To this end, the derivation of each method is given in detail without omitting auxiliary calculations or intermediate steps.…

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. In English.

Condición: As New. Unread book in perfect condition.

Hardback. Condición: New.

Hardcover. Condición: Brand New. 300 pages. 9.21x6.14x0.71 inches. In Stock.

Hardback. Condición: New. With the rise of digitalization, AI and modern data communication, engineering is increasingly challenged by the complexity of systems-of-systems, in which perception sensors have their own processing mechanism, information is merged at some centric entity, and cross-platform exchange of data is conceptualized in a holistic approach. Therefore, distributed architectures for data fusion, state estimation, and multi target tracking have been becoming increasingly important. The use of multiple sensors to perceive and compute the situational awareness picture leads to the generation of vast amounts of data, which need to be filtered, enriched, interpreted, and evaluated. This becomes infeasible without the notion of distributed algorithms. Theory and Methods for Distributed Data Fusion Applications first covers the fundamentals of stochastic motion, which constitutes the underlying models in target tracking and parameter estimation. The next chapter exposes the most important basic target tracking and state estimation algorithms and in the next those methods are extended to the estimation of full trajectories with states from multiple time stamps. Then the book introduces the problem of distributed fusion and presents first solutions to it. Then the final 3 chapters cover track fusion methods with unknown cross covariances, the Distributed Kalman Filter and its variants and finally methods for track-to-track association. This book is designed to provide state-of-the-art approaches and algorithms to the interested engineer for data fusion in distributed systems providing a profound understanding of the constraints, assumptions, benefits, and drawbacks. To this end, the derivation of each method is given in detail without omitting auxiliary calculations or intermediate steps.…

Condición: New. In English.

Hardback. Condición: New. With the rise of digitalization, AI and modern data communication, engineering is increasingly challenged by the complexity of systems-of-systems, in which perception sensors have their own processing mechanism, information is merged at some centric entity, and cross-platform exchange of data is conceptualized in a holistic approach. Therefore, distributed architectures for data fusion, state estimation, and multi target tracking have been becoming increasingly important. The use of multiple sensors to perceive and compute the situational awareness picture leads to the generation of vast amounts of data, which need to be filtered, enriched, interpreted, and evaluated. This becomes infeasible without the notion of distributed algorithms. Theory and Methods for Distributed Data Fusion Applications first covers the fundamentals of stochastic motion, which constitutes the underlying models in target tracking and parameter estimation. The next chapter exposes the most important basic target tracking and state estimation algorithms and in the next those methods are extended to the estimation of full trajectories with states from multiple time stamps. Then the book introduces the problem of distributed fusion and presents first solutions to it. Then the final 3 chapters cover track fusion methods with unknown cross covariances, the Distributed Kalman Filter and its variants and finally methods for track-to-track association. This book is designed to provide state-of-the-art approaches and algorithms to the interested engineer for data fusion in distributed systems providing a profound understanding of the constraints, assumptions, benefits, and drawbacks. To this end, the derivation of each method is given in detail without omitting auxiliary calculations or intermediate steps.…

Hardback. Condición: New.

Buch. Condición: Neu. Neuware - With the rise of digitalization, AI and modern data communication, engineering is increasingly challenged by the complexity of systems-of-systems, in which perception sensors have their own processing mechanism, information is merged at some centric entity, and cross-platform exchange of data is conceptualized in a holistic approach. Therefore, distributed architectures for data fusion, state estimation, and multi target tracking have been becoming increasingly important. The use of multiple sensors to perceive and compute the situational awareness picture leads to the generation of vast amounts of data, which need to be filtered, enriched, interpreted, and evaluated. This becomes infeasible without the notion of distributed algorithms. Theory and Methods for Distributed Data Fusion Applications first covers the fundamentals of stochastic motion, which constitutes the underlying models in target tracking and parameter estimation. The next chapter exposes the most important basic target tracking and state estimation algorithms and in the next those methods are extended to the estimation of full trajectories with states from multiple time stamps. Then the book introduces the problem of distributed fusion and presents first solutions to it. Then the final 3 chapters cover track fusion methods with unknown cross covariances, the Distributed Kalman Filter and its variants and finally methods for track-to-track association. This book is designed to provide state-of-the-art approaches and algorithms to the interested engineer for data fusion in distributed systems providing a profound understanding of the constraints, assumptions, benefits, and drawbacks. To this end, the derivation of each method is given in detail without omitting auxiliary calculations or intermediate steps.…

Hardback. Condición: New. With the rise of digitalization, AI and modern data communication, engineering is increasingly challenged by the complexity of systems-of-systems, in which perception sensors have their own processing mechanism, information is merged at some centric entity, and cross-platform exchange of data is conceptualized in a holistic approach. Therefore, distributed architectures for data fusion, state estimation, and multi target tracking have been becoming increasingly important. The use of multiple sensors to perceive and compute the situational awareness picture leads to the generation of vast amounts of data, which need to be filtered, enriched, interpreted, and evaluated. This becomes infeasible without the notion of distributed algorithms. Theory and Methods for Distributed Data Fusion Applications first covers the fundamentals of stochastic motion, which constitutes the underlying models in target tracking and parameter estimation. The next chapter exposes the most important basic target tracking and state estimation algorithms and in the next those methods are extended to the estimation of full trajectories with states from multiple time stamps. Then the book introduces the problem of distributed fusion and presents first solutions to it. Then the final 3 chapters cover track fusion methods with unknown cross covariances, the Distributed Kalman Filter and its variants and finally methods for track-to-track association. This book is designed to provide state-of-the-art approaches and algorithms to the interested engineer for data fusion in distributed systems providing a profound understanding of the constraints, assumptions, benefits, and drawbacks. To this end, the derivation of each method is given in detail without omitting auxiliary calculations or intermediate steps.…

Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnSensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their comp.…

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some 'awareness' of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not. 128 pp. Englisch.…

HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some 'awareness' of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.…

Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Buch. Condición: Neu. Introduction and Implementations of the Kalman Filter | Felix Govaers | Buch | Gebunden | Englisch | 2019 | IntechOpen | EAN 9781838805364 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …