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Multisensor Fusion Estimation Theory and Application
Multisensor Fusion Estimation Theory and Application
Knygos.lt klubas Knygos.lt nariams
313,05 €
-15%
Įprastai
368,29 €
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This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithm…
  • Leidėjas:
  • ISBN-10: 9811594252
  • ISBN-13: 9789811594250
  • Formatas: 15.6 x 23.4 x 1.6 cm, kieti viršeliai
  • Kalba: Anglų

Multisensor Fusion Estimation Theory and Application (el. knyga) (skaityta knyga) | knygos.lt

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This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithms under event-triggered mechanisms are introduced. Part IV consists of two chapters, in which fusion estimation for systems with non-Gaussian but heavy-tailed noises are introduced. The book is primarily intended for researchers and engineers in the field of data fusion and state estimation. It also benefits for both graduate and undergraduate students who are interested in target tracking, navigation, networked control, etc.

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  • Autorius: Liping Yan
  • Leidėjas:
  • ISBN-10: 9811594252
  • ISBN-13: 9789811594250
  • Formatas: 15.6 x 23.4 x 1.6 cm, kieti viršeliai
  • Kalba: Anglų

This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithms under event-triggered mechanisms are introduced. Part IV consists of two chapters, in which fusion estimation for systems with non-Gaussian but heavy-tailed noises are introduced. The book is primarily intended for researchers and engineers in the field of data fusion and state estimation. It also benefits for both graduate and undergraduate students who are interested in target tracking, navigation, networked control, etc.

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