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Kalman Filtering and Information Fusion, Hongbin Ma; Liping Yan; Yuanqing Xia; Mengyin Fu


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Автор: Hongbin Ma; Liping Yan; Yuanqing Xia; Mengyin Fu
Название:  Kalman Filtering and Information Fusion
ISBN: 9789811508059
Издательство: Springer
Классификация:






ISBN-10: 9811508054
Обложка/Формат: Hardcover
Страницы: 291
Вес: 0.64 кг.
Дата издания: 2020
Язык: English
Издание: 1st ed. 2020
Иллюстрации: 50 tables, color; 38 illustrations, color; 63 illustrations, black and white; xvii, 291 p. 101 illus., 38 illus. in color.
Размер: 234 x 156 x 19
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:
This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the greatest discoveries of the 20th century. It introduces readers to issues concerning various uncertainties in a single plant, and to corresponding solutions based on adaptive estimation. Further, it discusses in detail the issues that arise when Kalman filtering technology is applied in multi-sensor systems and/or multi-agent systems, especially when various sensors are used in systems like intelligent robots, autonomous cars, smart homes, smart buildings, etc., requiring multi-sensor information fusion techniques. Furthermore, when multiple agents (subsystems) interact with one another, it produces coupling uncertainties, a challenging issue that is addressed here with the aid of novel decentralized adaptive filtering techniques.
Overall, the book’s goal is to provide readers with a comprehensive investigation into the challenging problem of making Kalman filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced, together with a wealth of novel findings. As such, it can be a good reference book for researchers whose work involves filtering and applications; yet it can also serve as a postgraduate textbook for students in mathematics, engineering, automation, and related fields.
To read this book, only a basic grasp of linear algebra and probability theory is needed, though experience with least squares, navigation, robotics, etc. would definitely be a plus.

Дополнительное описание:
Preface.- Part I Kalman Filtering: Preliminaries.- Part II Kalman Filtering for Uncertain Systems.- Part III Kalman Filtering for Multi-Sensor Systems.- Part IV Kalman Filtering for Multi-Agent Systems.




Fundamentals of Stochastic Filtering

Автор: Alan Bain; Dan Crisan
Название: Fundamentals of Stochastic Filtering
ISBN: 1441926429 ISBN-13(EAN): 9781441926425
Издательство: Springer
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Цена: 13275.00 р.
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Описание: This book provides a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. While no prior knowledge of stochastic filtering is required, readers are assumed to be familiar with measure theory, probability theory and the basics of stochastic processes.

Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems

Автор: Xiao-Heng Chang
Название: Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems
ISBN: 3642551068 ISBN-13(EAN): 9783642551062
Издательство: Springer
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Цена: 15372.00 р.
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Описание: "Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique.

Kalman Filtering: Theory and Practice with MATLAB

Автор: Mohinder S. Grewal,Angus P. Andrews
Название: Kalman Filtering: Theory and Practice with MATLAB
ISBN: 1118851218 ISBN-13(EAN): 9781118851210
Издательство: Wiley
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Цена: 18050.00 р.
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Описание: The definitive textbook and professional reference on Kalman Filtering fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering.

Nonlinear Kalman Filtering for Force-Controlled Robot Tasks

Автор: Tine Lefebvre; Herman Bruyninckx; Joris de Schutte
Название: Nonlinear Kalman Filtering for Force-Controlled Robot Tasks
ISBN: 3642066291 ISBN-13(EAN): 9783642066290
Издательство: Springer
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Цена: 19589.00 р.
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Описание: "Nonlinear Kalman Filtering for Force-Controlled Robot Tasks " discusses the latest developments in the areas of contact modeling, nonlinear parameter estimation and task plan optimization for improved estimation accuracy.

Kalman filtering

Автор: Chui, Charles K. Chen, Guanrong
Название: Kalman filtering
ISBN: 3319476106 ISBN-13(EAN): 9783319476100
Издательство: Springer
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Цена: 8384.00 р.
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Описание: Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals.

Kalman Filtering

Автор: Charles K. Chui; Guanrong Chen
Название: Kalman Filtering
ISBN: 3642099661 ISBN-13(EAN): 9783642099663
Издательство: Springer
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Цена: 8487.00 р.
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Описание: This book presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method and an indirect method.

Robust Kalman Filtering for Signals and Systems with Large Uncertainties

Автор: Ian R. Petersen; Andrey V. Savkin
Название: Robust Kalman Filtering for Signals and Systems with Large Uncertainties
ISBN: 1461272092 ISBN-13(EAN): 9781461272090
Издательство: Springer
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Цена: 13060.00 р.
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Описание: Although the issue of robustness in filtering is not as critical as in feedback control (where there is always the issue of instability to worry about), research on robust filtering and state estimation has remained very active in recent years.

Time-Dependent Switched Discrete-Time Linear Systems: Control and Filtering

Автор: Lixian Zhang; Yanzheng Zhu; Peng Shi; Qiugang Lu
Название: Time-Dependent Switched Discrete-Time Linear Systems: Control and Filtering
ISBN: 3319288490 ISBN-13(EAN): 9783319288499
Издательство: Springer
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Цена: 18284.00 р.
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Описание: This book focuses on the basic control and filtering synthesis problems for discrete-time switched linear systems under time-dependent switching signals.

Theory of Affine Projection Algorithms for Adaptive Filtering

Автор: Kazuhiko Ozeki
Название: Theory of Affine Projection Algorithms for Adaptive Filtering
ISBN: 4431557377 ISBN-13(EAN): 9784431557371
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book focuses on theoretical aspects of the affine projection algorithm (APA) for adaptive filtering.

Adaptive Control, Filtering, and Signal Processing

Автор: K.J. Astr?m; G.C. Goodwin; P.R. Kumar
Название: Adaptive Control, Filtering, and Signal Processing
ISBN: 1461264391 ISBN-13(EAN): 9781461264392
Издательство: Springer
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Цена: 20962.00 р.
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Описание: The area of adaptive systems, which encompasses recursive identification, adaptive control, filtering, and signal processing, has been one of the most active areas of the past decade.

Nonlinear Filtering

Автор: Kumar Pakki Bharani Chandra; Da-Wei Gu
Название: Nonlinear Filtering
ISBN: 3030017966 ISBN-13(EAN): 9783030017965
Издательство: Springer
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Цена: 16769.00 р.
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Описание: This book gives readers in-depth know-how on methods of state estimation for nonlinear control systems. It starts with an introduction to dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation techniques for nonlinear systems are discussed, including the extended, unscented and cubature Kalman filters. The cubature Kalman filter and its variants are introduced in particular detail because of their efficiency and their ability to deal with systems with Gaussian and/or non-Gaussian noise. The book also discusses information-filter and square-root-filtering algorithms, useful for state estimation in some real-time control system design problems. A number of case studies are included in the book to illustrate the application of various nonlinear filtering algorithms. Nonlinear Filtering is written for academic and industrial researchers, engineers and research students who are interested in nonlinear control systems analysis and design. The chief features of the book include: dedicated coverage of recently developed nonlinear, Jacobian-free, filtering algorithms; examples illustrating the use of nonlinear filtering algorithms in real-world applications; detailed derivation and complete algorithms for nonlinear filtering methods, which help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB® codes associated with case-study applications, which can be downloaded from the Springer Extra Materials website.

Numerical Studies in Nonlinear Filtering

Автор: Y. Yavin
Название: Numerical Studies in Nonlinear Filtering
ISBN: 3540139583 ISBN-13(EAN): 9783540139584
Издательство: Springer
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Цена: 12157.00 р.
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