access icon free Extended formulation for unscented transform and its application as Monte Carlo alternative

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.

Inspec keywords: transforms; probability; Monte Carlo methods

Other keywords: Monte Carlo technique substitution; unscented transform calculation; probability functions; random variable probability distribution; nonlinear transformations; statistical moment estimation

Subjects: Monte Carlo methods; Monte Carlo methods; Statistics; Probability theory, stochastic processes, and statistics; Integral transforms; Function theory, analysis; Integral transforms

References

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http://iet.metastore.ingenta.com/content/journals/10.1049/el.2016.2867
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