This work considers methods for imposing sparsity in Bayesian regression with applications nonlinear system identification. We first review automatic relevance determination (ARD) and analytically demonstrate the need to additional regularization or thresholding achieve sparse models. then discuss two classes of methods, based based, which build on ARD learn parsimonious solutions linear proble...