Power Spectrum Estimation in Innovation Models by Nuclear Norm Optimization

AKÇAY H., TÜRKAY S.

14th IEEE International Conference on Control and Automation (ICCA), Alaska, United States Of America, 12 - 15 June 2018, pp.662-667 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icca.2018.8444313
  • City: Alaska
  • Country: United States Of America
  • Page Numbers: pp.662-667
  • Keywords: system identification, power spectrum, subspace method, regularization, innovation model, missing data, SYSTEM-IDENTIFICATION, RANK MINIMIZATION
  • Anadolu University Affiliated: Yes

Abstract

In this paper, identification of discrete-time power spectra of multi-input/multi-output models in innovation form from output-only time-domain measurements is studied. Two regularized nuclear norm minimization-based subspace algorithms are proposed. One of the algorithms is capable of handling missing data.