Achieving widetilde{O}(1/epsilon) Sample Complexity for Bilinear Systems Identification under Bounded Noises

arXiv:2603.20819v2 Announce Type: replace Abstract: This paper studies finite-sample set-membership identification for discrete-time bilinear systems under bounded symmetric log-concave disturbances. Our analysis considers trajectory-dependent regressors and allows marginally stable dynamics with polynomial mean-square state growth. We prove that the diameter of the feasible parameter set shrinks with sample complexity widetilde{mathcal O}(1/epsilon) where epsilon is the estimation error. Simulation supports the theory and illustrates the advantage of the proposed estimator for uncertainty quantification.

Source: arXiv cs.LG | 2026-06-23