离散化多维扩散过程模型的稳定性及其在模型约简中的应用

Weiqi Zhang, Kentaro Hirata, Yukinori Nakamura, Kunihisa Okano
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引用次数: 0

摘要

本文给出了离散扩散过程模型的一些稳定性注意事项。动机源于我们对一维模型模型简化过程中稳定性保持特性的观察。在对非降阶模型进行稳定性分析之前,将状态空间模型系统地扩展到多维情况。这个公式和相应的稳定性分析是这里的第一个重要贡献。然后阐明了保稳性背后的事实。因此,可以采用基于主成分分析等技术的任意大小的降阶模型,而不必考虑其稳定性。通过一维和二维的数值算例证明了这种约简方法的有效性。
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Stability Remarks on Discretized Multi-dimensional Diffusion Process Models and its Application to Model Reduction
This paper presents some stability remarks on the discretized diffusion process models. The motivation arises from our observation of stability preserving property in terms of a model reduction procedure of the 1D model. Before the stability analysis of the non-reduced order model, the state-space model is extended to multi-dimensional cases in a systematic manner. This formulation and the corresponding stability analysis are the first non-trivial contributions here. Then we clarify the fact behind the stability preserving property. As a consequence, one can employ arbitrary size of reduced order model based on the techniques such as the principal component analysis without any concern for the stability. The power of this reduction method is demonstrated via numerical examples for the 1D and 2D cases.
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