Titlebook: State Estimation for Nonlinear Continuous–Discrete Stochastic Systems; Numerical Aspects an Gennady Yu. Kulikov,Maria V. Kulikova Book 2024

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Kalman Filtering for Linear Stochastic Modeling Taskstry-and-positivity-loss in the fashion of square-root filtering methods. Two square-rooting schemes are explored and justified, here. The theoretical analysis of Kalman filters under consideration, which are summarized in the form of pseudo-codes situated in the appendix of this chapter, is accompan

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Gaussian Filtering with Deterministically Sampled Expectation and Covariance and rounding operations involved in computer-based simulations. Under some circumstances, such numerical integration and round-off errors committed may affect severely the calculation and result in non-symmetric and/or indefinite covariances yielded, which demolish the theoretical rigor of Kalman f

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Gaussian Filtering for Stiff Continuous–Discrete Stochastic Modeling Tasksocedures for treating stiff continuous–discrete stochastic systems in practice. The theoretical analysis of .-stable Gaussian filters with deterministically sampled expectation and covariance, which are summarized in the form of pseudo-codes placed in appendixes of Chaps. ., . and this chapter, is s

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