On Non-Gaussian Stochastic Parametrization

被引:0
|
作者
Dewilde, Patrick [1 ]
机构
[1] IEEE Life Fellow, Piscataway, NJ USA
关键词
parametrization; stochastic variables; non-Gaussian; stochastic modeling; multivariable orthogonalization;
D O I
10.1109/SPSYMPO51155.2020.9593873
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The paper addresses the question of parametrization with independent parameters for a multi-variable, non-Gaussian set of stochastic variables, based on higher order moments. The issue is particularly relevant for the construction of low-complexity models that meet measured correlation data between powers of the variables. It turns out that such a parametrization exists in the case where the correlation data is stricty ordered by increasing degree, and the paper shows in outline how it can be constructed.
引用
收藏
页码:46 / 51
页数:6
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