We propose a strategy for greedy sampling in the context of non-intrusive interpolation-based surrogate modeling for frequency-domain problems. We rely on a non-intrusive and cheap error indicator to drive the adaptive selection of the high-fidelity samples on which the surrogate is based. We develop a theoretical framework to support our proposed indicator. We also present several practical approaches for the termination criterion that is used to end the greedy sampling iterations. To showcase our greedy strategy, we numerically test it in combination with the well-known Loewner framework. To this effect, we consider several benchmarks, highlighting the effectiveness of our adaptive approach in approximating the transfer function of complex systems from a few samples.

我们提出了一种在频域问题的非侵入式基于插值的代理建模背景下的贪婪采样策略。我们依靠非侵入性且廉价的错误指示器来驱动代理所基于的高保真样本的自适应选择。我们开发了一个理论框架来支持我们提出的指标。我们还提出了几种用于结束贪婪采样迭代的终止标准的实用方法。为了展示我们的贪婪策略，我们结合著名的 Loewner 框架对其进行了数值测试。为此，我们考虑了几个基准，强调了我们的自适应方法在从几个样本中逼近复杂系统的传递函数方面的有效性。