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EmrysFilter 0.1.0
State estimation utilities in C++23 using Eigen
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The root form of a linearization (decisions.md [linearization-forms]), which every sigma-point method computes: the root \( S \) of the marked input's covariance that spread the points, \( S S^T = P \), and the whitened cross-covariance \( \Psi = S^{-1} \Sigma_{xy} = (H S)^T \), the weighted sum \( \sum_i w_i \xi_i \Delta y_i^T \) over the unit points \( \xi_i \) and the output deviations \( \Delta y_i \). More...
#include <EmrysFilter/Models/Linearization.h>
The root form of a linearization (decisions.md [linearization-forms]), which every sigma-point method computes: the root \( S \) of the marked input's covariance that spread the points, \( S S^T = P \), and the whitened cross-covariance \( \Psi = S^{-1} \Sigma_{xy} = (H S)^T \), the weighted sum \( \sum_i w_i \xi_i \Delta y_i^T \) over the unit points \( \xi_i \) and the output deviations \( \Delta y_i \).
OutputWithCross names it, and the method fixes it, as JacobianForm's does.