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Nonlinear filtering = methods and ap...

Chandra, Kumar Pakki Bharani.

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Nonlinear filtering = methods and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nonlinear filtering/ by Kumar Pakki Bharani Chandra, Da-Wei Gu.
Reminder of title:	methods and applications /
Author:	Chandra, Kumar Pakki Bharani.
other author:	Gu, Da-Wei.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xix, 184 p. :ill., digital ;24 cm.
[NT 15003449]:	Linear and Nonlinear Control Systems -- State Estimation and Prediction -- Linear Estimation Techniques -- Jacobian-Based Filters -- Unscented Kalman Filters -- Cubature Kalman Filters -- Variants of Cubature Kalman Filters -- Robustness Consideration of Filtering Algorithms.
Contained By:	Springer eBooks
Subject:	Stochastic processes. -
Online resource:	https://doi.org/10.1007/978-3-030-01797-2
ISBN:	9783030017972

Nonlinear filtering = methods and applications /
Chandra, Kumar Pakki Bharani.

Nonlinear filteringmethods and applications /[electronic resource] :by Kumar Pakki Bharani Chandra, Da-Wei Gu. - Cham :Springer International Publishing :2019. - xix, 184 p. :ill., digital ;24 cm.

Linear and Nonlinear Control Systems -- State Estimation and Prediction -- Linear Estimation Techniques -- Jacobian-Based Filters -- Unscented Kalman Filters -- Cubature Kalman Filters -- Variants of Cubature Kalman Filters -- Robustness Consideration of Filtering Algorithms.

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, etc. 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 help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB® codes associated with case-study applications can be downloaded from the Springer Extra Materials website.

ISBN: 9783030017972

Standard No.: 10.1007/978-3-030-01797-2doiSubjects--Topical Terms:

520663
Stochastic processes.

LC Class. No.: QA274 / .C436 2019

Dewey Class. No.: 519.23

Nonlinear filtering = methods and applications /
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100 1 $a Chandra, Kumar Pakki Bharani. $3 3381748
245 1 0 $a Nonlinear filtering $h [electronic resource] : $b methods and applications / $c by Kumar Pakki Bharani Chandra, Da-Wei Gu.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xix, 184 p. : $b ill., digital ; $c 24 cm.
505 0 $a Linear and Nonlinear Control Systems -- State Estimation and Prediction -- Linear Estimation Techniques -- Jacobian-Based Filters -- Unscented Kalman Filters -- Cubature Kalman Filters -- Variants of Cubature Kalman Filters -- Robustness Consideration of Filtering Algorithms.
520 $a 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, etc. 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 help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB® codes associated with case-study applications can be downloaded from the Springer Extra Materials website.
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650 0 $a Filters (Mathematics) $3 556522
650 1 4 $a Control and Systems Theory. $3 3381515
650 2 4 $a Signal, Image and Speech Processing. $3 891073
700 1 $a Gu, Da-Wei. $3 896765
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950 $a Intelligent Technologies and Robotics (Springer-42732)