@inproceedings{228d0cc5d7d3443b8932a74cf173bd64,
title = "State covariances and the matrix completion problem",
abstract = "State statistics of a linear system obey certain structural constraints that arise from the underlying dynamics and the directionality of input disturbances. Herein, we formulate completion problems of partially known state statistics with the added freedom of identifying disturbance dynamics. The goal of the proposed completion problem is to obtain information about input excitations that explain observed sample statistics. Our formulation aims at low-complexity models for admissible disturbances. The complexity represents the dimensionality of the subspace of the state-dynamics that is directly affected by disturbances. An example is provided to illustrate that colored-in-time stochastic processes can be effectively used to explain available data.",
keywords = "Convex optimization, Low-rank approximation, Noise statistics, Nuclear norm regularization, State covariances, Structured matrix completion problems",
author = "Yongxin Chen and Mihailo Jovanovic and Georgiou, {Tryphon T}",
year = "2013",
doi = "10.1109/CDC.2013.6760127",
language = "English (US)",
isbn = "9781467357173",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1702--1707",
booktitle = "2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013",
note = "52nd IEEE Conference on Decision and Control, CDC 2013 ; Conference date: 10-12-2013 Through 13-12-2013",
}