Segmentation of ARX-Models Using Sum-of-Norms Regularization

H. Ohlsson, L. Ljung, and S. Boyd

Automatica, 46(6):1107-1111, June 2010.

Segmentation of time-varying systems and signals into models whose parameters are piecewise constant in time is an important and well studied problem. It is here formulated as a least-squares problem with sum-of-norms regularization over the state parameter jumps, a generalization of ell_1-regularization. A nice property of the suggested formulation is that it only has one tuning parameter, the regularization constant which is used to trade off fit and the number of segments.