Zobrazeno 1 - 10
of 20 045
pro vyhledávání: '"Nonlinear system identification"'
The Fisher Information Matrix (FIM) provides a way for quantifying the information content of an observable random variable concerning unknown parameters within a model that characterizes the variable. When parameters in a model are directly linked t
Externí odkaz:
http://arxiv.org/abs/2406.05395
Nonlinear system identification remains an important open challenge across research and academia. Large numbers of novel approaches are seen published each year, each presenting improvements or extensions to existing methods. It is natural, therefore
Externí odkaz:
http://arxiv.org/abs/2405.10779
This paper introduces a novel optimization-based approach for parametric nonlinear system identification. Building upon the prediction error method framework, traditionally used for linear system identification, we extend its capabilities to nonlinea
Externí odkaz:
http://arxiv.org/abs/2403.17858
In engineering, accurately modeling nonlinear dynamic systems from data contaminated by noise is both essential and complex. Established Sequential Monte Carlo (SMC) methods, used for the Bayesian identification of these systems, facilitate the quant
Externí odkaz:
http://arxiv.org/abs/2404.12923
Autor:
Bemporad, Alberto
In this paper, we propose a very efficient numerical method based on the L-BFGS-B algorithm for identifying linear and nonlinear discrete-time state-space models, possibly under $\ell_1$- and group-Lasso regularization for reducing model complexity.
Externí odkaz:
http://arxiv.org/abs/2403.03827
This study designs and evaluates multiple nonlinear system identification techniques for modeling the UAV swarm system in planar space. learning methods such as RNNs, CNNs, and Neural ODE are explored and compared. The objective is to forecast future
Externí odkaz:
http://arxiv.org/abs/2311.12906