Current browse context:
eess.SY
Change to browse by:
References & Citations
Electrical Engineering and Systems Science > Systems and Control
Title: Estimation Sample Complexity of a Class of Nonlinear Continuous-time Systems
(Submitted on 8 Dec 2023 (v1), last revised 22 Apr 2024 (this version, v2))
Abstract: We present a method of parameter estimation for large class of nonlinear systems, namely those in which the state consists of output derivatives and the flow is linear in the parameter. The method, which solves for the unknown parameter by directly inverting the dynamics using regularized linear regression, is based on new design and analysis ideas for differentiation filtering and regularized least squares. Combined in series, they yield a novel finite-sample bound on mean absolute error of estimation.
Submission history
From: Simon Kuang [view email][v1] Fri, 8 Dec 2023 21:42:11 GMT (332kb,D)
[v2] Mon, 22 Apr 2024 22:03:37 GMT (456kb,D)
Link back to: arXiv, form interface, contact.