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EmrysFilter 0.1.0
State estimation utilities in C++23 using Eigen
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The parameters of the scaled unscented transform over a number of coordinates, in Scalar, as an UnscentedRule gives them: \( \lambda = \alpha^2 (L + \kappa) - L \). More...
#include <EmrysFilter/Models/Methods.h>
Public Attributes | |
| Scalar | alpha |
| the spread of the points about the mean | |
| Scalar | beta |
| the center point's extra covariance weight | |
| Scalar | kappa |
| the secondary scaling | |
The parameters of the scaled unscented transform over a number of coordinates, in Scalar, as an UnscentedRule gives them: \( \lambda = \alpha^2 (L + \kappa) - L \).