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State Estimation for Nonlinear Continuous–Discrete Stochastic Systems Numerical Aspects and Implementation Issues /

This book addresses the problem of accurate state estimation in nonlinear continuous-time stochastic models with additive noise and discrete measurements. Its main focus is on numerical aspects of computation of the expectation and covariance in Kalman-like filters rather than on statistical propert...

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Dades bibliogràfiques
Autors principals: Kulikov, Gennady Yu (Autor), Kulikova, Maria V. (Autor)
Autor corporatiu: SpringerLink (Online service)
Format: Electrònic eBook
Idioma:anglès
Publicat: Cham : Springer International Publishing : Imprint: Springer, 2024.
Edició:1st ed. 2024.
Col·lecció:Studies in Systems, Decision and Control, 539
Matèries:
Control engineering.
System theory.
Control theory.
Signal processing.
Control and Systems Theory.
Systems Theory, Control.
Digital and Analog Signal Processing.
Accés en línia:https://doi.org/10.1007/978-3-031-61371-5
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Taula de continguts:
  • Numerical Integration Methods for Ordinary Differential Equations
  • Kalman Filtering for Linear Stochastic Modeling
  • Extended Kalman Filtering for Nonlinear Stochastic Modeling
  • Unscented Kalman Filtering for Nonlinear Stochastic Modeling
  • Cubature Kalman Filtering for Nonlinear Stochastic Modeling
  • Kalman-Like Filtering for Stiff Stochastic Modeling.

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