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English(EN) Characterization of Thermal Systems from Noisy and Low-resolution Measurements Using Dynamic Mode Decomposition

动态模式分解应用于噪声热力系统数据

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新研究论文探讨了动态模式分解（DMD）在分析具有噪声和低分辨率数据的热力系统中的应用。该研究考察了预处理和截断策略如何在这些挑战性条件下提高DMD的稳定性和可解释性。结果表明，当仔细选择保留模式的数量，平衡重建保真度和噪声敏感性时，DMD可以有效地从稀疏和退化的数据集中捕获主导的热力行为。 AI

排序理由 一篇在arXiv上发表的研究论文，详细介绍了一种计算物理学方法。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.LG 阅读 →

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动态模式分解应用于噪声热力系统数据

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一篇在arXiv上发表的研究论文，详细介绍了一种计算物理学方法。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · M. E. P. Silva, L. S. Araujo, F. T. Colombo, A. Cunha Jr, S. da Silva ·

    使用动态模式分解对来自噪声和低分辨率测量数据的热力系统进行表征

    arXiv:2608.14581v1 Announce Type: cross Abstract: Thermal monitoring in practical applications is often constrained by sparse sensing, measurement noise, and limited spatial resolution, which hinder the identification of heat transfer dynamics. In such settings, calibrating high-…

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