A cost-aware space-filling input design method using Gaussian processes for nonlinear system identification that reduces experimental cost while preserving model performance.
Authorea , year=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
eess.SY 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Least Costly Space-Filling Experiment Design for the Identification of a Nonlinear System
A cost-aware space-filling input design method using Gaussian processes for nonlinear system identification that reduces experimental cost while preserving model performance.