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A Kalman filter primer

Eubank (mathematics and statistics, Arizona State U.) offers a self-contained, concise rigorous derivation of all the basic Kalman filter recursions from first principles. He lays out the basic prediction problem for signal-plus-noise models, deriving the Gramm-Schmidt algorithm and Cholesky decomposition. He covers the fundamental covariance struc.

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  • "Eubank (mathematics and statistics, Arizona State U.) offers a self-contained, concise rigorous derivation of all the basic Kalman filter recursions from first principles. He lays out the basic prediction problem for signal-plus-noise models, deriving the Gramm-Schmidt algorithm and Cholesky decomposition. He covers the fundamental covariance struc."@en

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  • "Ressources Internet"
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  • "A Kalman filter primer"
  • "A Kalman filter primer"@en
  • "A Kalman Filter Primer"@en

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