A parametric data-driven model built with p-AAA reduces relative force estimation error by nearly 38% versus the best non-parametric model while generalizing across load amplitudes and input waveforms.
Data-driven parame trized model reduction in the Loewner framework,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
math.DS 1years
2026 1verdicts
UNVERDICTED 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Load Identification in Bistable Spacecraft Booms via Parametric Data-Driven Modeling
A parametric data-driven model built with p-AAA reduces relative force estimation error by nearly 38% versus the best non-parametric model while generalizing across load amplitudes and input waveforms.