The role of rank penalties in linear system identification. Issue 28 (2015) - Prando, G.; Pillonetto, G.; Chiuso, A.
Abstract: We discuss the linear system identification methods that are based on a regularized estimation problem including a rank penalty (typically formulated in terms of nuclear norm).We provide a common framework, under which most of these procedures can be recast. Following the Bayesian approach to system identification, we also introduce a Gaussian prior inducing a rank penalty and we prove the effectiveness of this method through a Monte-Carlo experiment.