Data fusion methods applications (28 risultati)
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Hardback. Condizione: 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 concep…tualized 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.
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Editore: Institution of Engineering and Technology, GB, 2023
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Hardback. Condizione: 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 concep…tualized 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.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 300 pages. 9.21x6.14x0.71 inches. In Stock.
Lingua: Inglese
Editore: Institution of Engineering and Technology, GB, 2023
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Da: Rarewaves USA United, OSWEGO, IL, U.S.A.Rarewaves USA United
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Hardback. Condizione: 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 concep…tualized 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.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on the development of multisensor fusion algorithms for wearable devices that are useful in ambulatory health monitoring using signal-processing and deep learning-based methods. The algorithms described account for the signal quality pr…ior to fusion, in order to enable reliable inferences without contributing to additional computational overhead. The content discussed is beneficial in the broad application of multisensor fusion, as the algorithms developed or discussed in the final chapters are generalized cases of the methods developed in the initial chapters, offering relevance to the broader multisensor fusion community.Provides a single-source reference to the development of fusion methods and analysis of fusion algorithmsTreats fusion as a signal-processing-based problem, applied to a wide variety of fusion applicationsDescribes a step-by-step methodology for development of a generalized fusion algorithm for any application.
Kernel-based Data Fusion for Machine Learning: Methods and Applications in Bioinformatics and Text Mining (Studies in Computational Intelligence, 345)
Yu, Shi; Tranchevent, Léon-Charles; Moor, Bart; Moreau, Yves
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Kernel-based Data Fusion for Machine Learning: Methods and Applications in Bioinformatics and Text Mining (Studies in Computational Intelligence, 345)
Yu, Shi; Tranchevent, Léon-Charles; Moor, Bart; Moreau, Yves
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Editore: Institution of Engineering and Technology, GB, 2023
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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Hardback. Condizione: 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 concep…tualized 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.
Altre immagini- Brossura
Da: preigu, Osnabrück, Germaniapreigu
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EUR 158,00
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Taschenbuch. Condizione: Neu. Kernel-based Data Fusion for Machine Learning | Methods and Applications in Bioinformatics and Text Mining | Shi Yu (u. a.) | Taschenbuch | Studies in Computational Intelligence | xiv | Englisch | 2013 | Springer | EAN 9783642267512 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergart…enstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2013
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 181,89
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins with a brief survey of additive models and Raylei…gh quotient objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem. The second part presents several novel kernel fusion algorithms and some real applications in supervised and unsupervised learning. The last part of the book substantiates the value of the proposed theories and algorithms in MerKator, an open software to identify disease relevant genes based on the integration of heterogeneous genomic data sources in multiple species. The topics presented in this book are meant for researchers or students who use support vector machines. Several topics addressed in the book may also be interesting to computational biologists who want to tackle data fusion challenges in real applications. The background required of the reader is a good knowledge of data mining, machine learning and linear algebra.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins with a brief survey of additive models and Rayleigh quot…ient objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem. The second part presents several novel kernel fusion algorithms and some real applications in supervised and unsupervised learning. The last part of the book substantiates the value of the proposed theories and algorithms in MerKator, an open software to identify disease relevant genes based on the integration of heterogeneous genomic data sources in multiple species. The topics presented in this book are meant for researchers or students who use support vector machines. Several topics addressed in the book may also be interesting to computational biologists who want to tackle data fusion challenges in real applications. The background required of the reader is a good knowledge of data mining, machine learning and linear algebra.
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Da: Buchpark, Trebbin, GermaniaBuchpark
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EUR 140,47
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Condizione: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins with a brief survey of additive models and Rayleigh quotie…nt objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem. The second part presents several novel kernel fusion algorithms and some real applications in supervised and unsupervised learning. The last part of the book substantiates the value of the proposed theories and algorithms in MerKator, an open software to identify disease relevant genes based on the integration of heterogeneous genomic data sources in multiple species. The topics presented in this book are meant for researchers or students who use support vector machines. Several topics addressed in the book may also be interesting to computational biologists who want to tackle data fusion challenges in real applications. The background required of the reader is a good knowledge of data mining, machine learning and linear algebra.
Kernel-Based Data Fusion for Machine Learning: Methods and Applications in Bioinformatics and Text Mining
Yu, Shi/ Tranchevent, Léon-charles/ Moor, Bart/ Moreau, Yves
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Kernel-based Data Fusion for Machine Learning: Methods and Applications in Bioinformatics and Text Mining (Studies in Computational Intelligence (345))
Yu, Shi, Tranchevent, Léon-Charles, Moor, Bart, Moreau, Yves
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Buch. Condizione: Neu. Deep Learning and Signal-Processing Methods for Multisensor Data Fusion | Applications to Ambulatory Health Monitoring | Arlene John (u. a.) | Buch | xxx | Englisch | 2026 | Springer | EAN 9783031967238 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[…dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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