Linear and nonlinear system identification under $\ell_1$- and group-Lasso regularization via L-BFGS-B

arXiv:2403.03827v1 Announce Type: cross
Abstract: In this paper, we propose an approach for identifying linear and nonlinear discrete-time state-space models, possibly under $\ell_1$- and group-Lasso regularization, based on the L-BFGS-B algorithm. For the identification of linear models, we show that, compared to classical linear subspace methods, the approach often provides better results, is much more general in terms of the loss and regularization terms used, and is also more stable from a numerical point of view. The proposed method not …

arxiv cs.lg cs.sy eess.sy identification lasso linear math.oc regularization type via