Spectrum estimation in innovation models by a nuclear norm optimization based algorithm


3rd IEEE Colombian Conference on Automatic Control (CCAC), Cartagena, Colombia, 18 - 20 October 2017 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Cartagena
  • Country: Colombia
  • Keywords: system identification, power spectrum, subspace method, nuclear norm, regularization, innovation model, FREQUENCY-DOMAIN, SYSTEM-IDENTIFICATION, RANK MINIMIZATION
  • Anadolu University Affiliated: Yes


In this paper, identification of multi-input/multioutput (Ml MO) state-space models in the innovation form by a regularized-nuclear norm optimization based subspace algorithm is studied. Parametrization issues arc carefully addressed for MIMO state-space models. The optimization problem formulated in this paper allows one to utilize a variety of norms in the objective function including the nuclear and the quadratic norms without affecting the parametrization results. A numerical example illustrates the results derived in the paper.