Kalman Filtering
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Kalman Filtering

Theory and Practice with MATLAB
 E-Book
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9781118984918
Veröffentl:
2014
Einband:
E-Book
Seiten:
640
Autor:
Mohinder S. Grewal
Serie:
Wiley - IEEE
eBook Typ:
EPUB
eBook Format:
Reflowable E-Book
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:

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. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
The definitive textbook and professional reference on KalmanFiltering - fully updated, revised, and expandedThis book contains the latest developments in the implementationand application of Kalman filtering. Authors Grewal and Andrewsdraw upon their decades of experience to offer an in-depthexamination of the subtleties, common pitfalls, and limitations ofestimation theory as it applies to real-world situations. Theypresent many illustrative examples including adaptations fornonlinear filtering, global navigation satellite systems, the errormodeling of gyros and accelerometers, inertial navigation systemsand freeway traffic control.Kalman Filtering: Theory and Practice Using MATLAB, FourthEdition is an ideal textbook in advanced undergraduate andbeginning graduate courses in stochastic processes and Kalmanfiltering. It is also appropriate for self-instruction or review bypracticing engineers and scientists who want to learn more aboutthis important topic.

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