State covariances and the matrix completion problem

被引:0
|
作者
Chen, Yongxin [1 ]
Jovanovic, Mihailo R. [1 ]
Georgiou, Tryphon T. [1 ]
机构
[1] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA
来源
2013 IEEE 52ND ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC) | 2013年
关键词
Convex optimization; low-rank approximation; nuclear norm regularization; state covariances; structured matrix completion problems; noise statistics; ENERGY AMPLIFICATION; LYAPUNOV; SPECTRUM; STEIN; POWER;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
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页码:1702 / 1707
页数:6
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