This paper presents a modified set theoretic framework for estimating the state of a linear dynamic system based on uncertain measurements.
Thomas Kailath: State-Space Modelling: Square Root Algorithms. Concise Encyclopedia of Modelling & Simulation 1992: 455-461. manage site settings.
Using our recent observation that H filtering coincides with Kalman filtering in Krein space we develop square- root arrays and Chandraskhar recursions for H∞ ...
Oct 22, 2024 · We present several new algorithms, and more generally a new approach, to recursive estimation algorithms for linear dynamical systems.
An eficient, approximate algorithm for square root Kalman filter is presented. Large-scale, space-time estimation can be performed sequentially over time by ...
Square root algorithms were originally proposed for a special case of Gaussian graphical models, the Kalman fil- ter or state space model. The idea is to ...
Apr 5, 2023 · Abstract. In this article, we first derive parallel square-root methods for state estimation in linear state-space models.
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Jan 5, 2017 · The essential idea behind the algorithm is to compute Pt=StS′t, as such a multiplication will always yield a symmetric non negative matrix.
Additionally, following the latest achievements in the KF community, all square-root algorithms are formulated here in the so-called array form. It implies the ...
The Morf-Kailath discrete square-root filtering algorithms are extended to incorporate sensitivity information with respect1 to the assumed model and.