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Covariance-Regulated Recursive Koopman Learning for Nonlinear Systems with Uncertain Time-Varying Dynamics
Offline models for autonomous robots often fail under time-varying dynamics outside their training distribution. While Koopman operator theory offers a linear representation of nonlinear dynamics via lifting, its transition to online recursive estimation may suffer numerical vulnerabilities: covaria
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