3 papers
cs.LG2026
Stability and Discretization Error of State Space Model Neural Operators
Abderrahim Bendahi, Adrien Fradin, Johan Peralez +2
Neural operators have emerged as a powerful, discretization-invariant framework for solving partial differential equations (PDEs). Although established approaches like the Deep Ope…
eess.SY2026
Learning a Contracting KKL-observer with Local Optimal Guarantees
Clara LucÃa Galimberti, Johan Peralez, Daniele Astolfi +2
The Kazantzis-Kravaris-Luenberger (KKL) observer provides a general framework for nonlinear state estimation by immersing the system dynamics into a stable linear or nonlinear late…
math.OC2026
Proximal observers for secure state estimation
Laurent Bako, Madiha Nadri, Vincent Andrieu +1
This paper discusses a general framework for designing robust state estimators for a class of discrete-time nonlinear systems. We consider systems that may be impacted by impulsive…