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Nonlinear Filtering - Methods and Applications (Hardcover, 1st ed. 2019)
Loot Price: R3,436
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Nonlinear Filtering - Methods and Applications (Hardcover, 1st ed. 2019)
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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 (R) codes associated with case-study applications, which
can be downloaded from the Springer Extra Materials website.
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