基于参数空间划分的高维变异性分析

2020 IEEE/MTT-S International Microwave Symposium (IMS) Pub Date : 2020-08-01 DOI:10.1109/IMS30576.2020.9224060

Y. Tao, F. Ferranti, M. Nakhla

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引用次数: 1

摘要

提出了一种基于随机配位的方法，用于随机参数较多的变异性分析。该方法基于节点撕裂概念，将随机参数的原始空间分解为低维子空间的组合。相关的数值结果验证了该方法的有效性和准确性。

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High-Dimensional Variability Analysis via Parameters Space Partitioning

A stochastic collocation-based method is proposed for variability analysis in the presence of relatively large number of stochastic parameters. The method is based on the node tearing concept where the original space of stochastic parameters is decomposed into a combination of lower dimension subspaces. Pertinent numerical results are presented to validate the efficiency and accuracy of the proposed technique.

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2020 IEEE/MTT-S International Microwave Symposium (IMS)

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