Characterization of Thermal Systems from Noisy and Low-resolution Measurements Using Dynamic Mode Decomposition

Excerpt

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-fidelity physical models is computationally demanding, motivating data-driven approaches. Dynamic Mode Decomposition (DMD) provides a framework for extracting spatiotemporal structures from measurement data, but its stan