Power Spectrum Estimation in Innovation Models by Nuclear Norm Optimization
14th IEEE International Conference on Control and Automation (ICCA), Alaska, United States Of America, 12 - 15 June 2018, pp.662-667, (Full Text)
- 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.