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stat.ME2025
Instrumental variables system identification with consistency
Simon Kuang, Xinfan Lin
Instrumental variables (eliminate the bias that afflicts least-squares identification of dynamical systems through noisy data, yet traditionally relies on external instruments that…
eess.SY2025
Assumed Density Filtering and Smoothing with Neural Network Surrogate Models
Simon Kuang, Xinfan Lin
The Kalman filter and Rauch-Tung-Striebel (RTS) smoother are optimal for state estimation in linear dynamic systems. With nonlinear systems, the challenge consists in how to propag…
eess.SY2025
Debiasing Continuous-time Nonlinear Autoregressions
Simon Kuang, Xinfan Lin
We study how to identify a class of continuous-time nonlinear systems defined by an ordinary differential equation affine in the unknown parameter. We define a notion of asymptotic…