Open AccessExtended formulation for unscented transform and its application as Monte Carlo alternative
Author(s) -
Medeiros J.E.G.,
Haddad S.A.P.,
Menezes L.R.A.X.
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2016.2867
Subject(s) - monte carlo method , unscented transform , moment (physics) , moment generating function , random variable , probability distribution , hybrid monte carlo , computer science , mathematics , nonlinear system , quasi monte carlo method , lomax distribution , mathematical optimization , algorithm , statistics , markov chain monte carlo , kalman filter , physics , classical mechanics , quantum mechanics , extended kalman filter , moving horizon estimation , pareto principle
A novel approach for the unscented transform calculation is detailed, showing a technique that can be used to obtain smoother estimates for probability functions based on Monte Carlo technique substitution. The method is computationally efficient for statistical moment estimation of nonlinear transformations and does not require full knowledge of the probability distribution of the random variables, being completely defined by its moments.