2 papers
eess.SY2020
Data-driven sparse sensor placement based on A-optimal design of experiment with ADMM
Takayuki Nagata, Taku Nonomura, Kumi Nakai +3
The present study proposes a sensor selection method based on the proximal splitting algorithm and the A-optimal design of experiment using the alternating direction method of mult…
eess.SP2020
Effect of Objective Function on Data-Driven Greedy Sparse Sensor Optimization
Kumi Nakai, Keigo Yamada, Takayuki Nagata +2
The selection problem of an optimal set of sensors estimating the snapshot of high-dimensional data is considered. The objective functions based on various criteria of optimal desi…