Neural Operator-Based Nonlinear Nudging for Chaotic Dynamical Systems
This work proposes neural network nudging, a data-driven method for learning nudging terms in nonlinear state space models and establishes a theoretical existence result based on the Kazantzis--Kravaris--Luenberger observer theory.
Jaemin Oh, Jinsil Lee, Youngjoon Hong
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