Stability of Discrete Empirical Interpolation and Gappy Proper Orthogonal Decomposition with Randomized and Deterministic Sampling Points

Stability of Discrete Empirical Interpolation and Gappy Proper Orthogonal Decomposition with Randomized and Deterministic Sampling Points
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随机和确定性采样点的离散经验插值和间隙本征正交分解的稳定性

DOI:
10.1137/19m1307391
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发表时间:
2020
影响因子:
3.1
通讯作者:
Gugercin, Serkan
Gugercin, Serkan
中科院分区:
数学2区
文献类型:
--
作者:
Peherstorfer, Benjamin;Drmač, Zlatko;Gugercin, Serkan

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这项工作研究了非线性模型简化和测量状态场近似的(离散)经验插值的稳定性。经验插值通过低维空间中的插值从一些样本(测量值)中得出近似值。据观察,如果样本由于噪声、湍流和数值不准确等原因受到扰动,经验插值可能会变得不稳定。这项工作的主要贡献是概率分析,表明如果样本是随机的并且使用的样本数量多于低维空间的维度,则可以获得稳定的近似值。过采样,即采用比低维空间的维度更多的采样点,通过回归产生近似值,并以间隙适当正交分解的名称为人所知。基于概率分析的见解,提出了一种确定性采样策略,旨在通过考虑低维空间的信息,以比随机采样更少的点实现较低的近似误差。根据燃烧过程的噪声测量和噪声存在下的模型简化来重建速度场的数值结果证明了经验插值的不稳定性以及带过采样的间隙本征正交分解的稳定性。
This work investigates the stability of (discrete) empirical interpolation for nonlinear model reduction and state field approximation from measurements. Empirical interpolation derives approximations from a few samples (measurements) via interpolation in low-dimensional spaces. It has been observed that empirical interpolation can become unstable if the samples are perturbed due to, e.g., noise, turbulence, and numerical inaccuracies. The main contribution of this work is a probabilistic analysis that shows that stable approximations are obtained if samples are randomized and if more samples than dimensions of the low-dimensional spaces are used. Oversampling, i.e., taking more sampling points than dimensions of the low-dimensional spaces, leads to approximations via regression and is known under the name of gappy proper orthogonal decomposition. Building on the insights of the probabilistic analysis, a deterministic sampling strategy is presented that aims to achieve lower approximation errors with fewer points than randomized sampling by taking information about the low-dimensional spaces into account. Numerical results of reconstructing velocity fields from noisy measurements of combustion processes and model reduction in the presence of noise demonstrate the instability of empirical interpolation and the stability of gappy proper orthogonal decomposition with oversampling.
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发表时间: 2018-02
期刊: SIAM J. Matrix Anal. Appl.
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作者:
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发表时间: 2016-01-01
影响因子: 3.1
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DOI: 10.1002/nme.3327
发表时间: 2012-04-27
影响因子: 2.9
作者:
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