TY  - EJOU
AU  - Saito, Yuji 
AU  - Yamada, Keigo 
AU  - Kanda, Naoki 
AU  - Nakai, Kumi 
AU  - Nagata, Takayuki 
AU  - Nonomura, Taku 
AU  - Asai, Keisuke 

TI  - Data-Driven Determinant-Based Greedy Under/Oversampling Vector Sensor Placement
T2  - Computer Modeling in Engineering \& Sciences

PY  - 2021
VL  - 129
IS  - 1
SN  - 1526-1506

AB  - A vector-measurement-sensor-selection problem in the undersampled and oversampled cases is considered by extending the previous novel approaches: a greedy method based on D-optimality and a noise-robust greedy method in this paper. Extensions of the vector-measurement-sensor selection of the greedy algorithms are proposed and applied to randomly generated systems and practical datasets of flowfields around the airfoil and global climates to reconstruct the full state given by the vector-sensor measurement.
KW  - Sparse sensor selection; vector-sensor measurement

DO  - 10.32604/cmes.2021.016603