85 citations · 479 across the 16 of their papers we have counts for
7 papers · 1 filter
Proof-of-concept Study of Sparse Processing Particle Image Velocimetry for Real Time Flow Observation
Naoki Kanda, Chihaya Abe, Shintaro Goto +5
In this paper, we overview, evaluate, and demonstrate the sparse processing particle image velocimetry (SPPIV) as a real-time flow field estimation method using the particle image…
Seismic Wavefield Reconstruction based on Compressed Sensing using Data-Driven Reduced-Order Model
Takayuki Nagata, Kumi Nakai, Keigo Yamada +5
A seismic wavefield reconstruction framework based on compressed sensing using the data-driven reduced-order model (ROM) is proposed and its characteristics are investigated throug…
Observation Site Selection for Physical Model Parameter Estimation toward Process-Driven Seismic Wavefield Reconstruction
Kumi Nakai, Takayuki Nagata, Keigo Yamada +5
The ``big'' seismic data not only acquired by seismometers but also acquired by vibrometers installed in buildings and infrastructure and accelerometers installed in smartphones wi…
Optimization of Sparse Sensor Placement for Estimation of Wind Direction and Surface Pressure Distribution Using Time-Averaged Pressure-Sensitive Paint Data on Automobile Model
Ryoma Inoba, Kazuki Uchida, Yuto Iwasaki +5
This study proposes a method for predicting the wind direction against the simple automobile model (Ahmed model) and the surface pressure distributions on it by using data-driven o…
Data-Driven Sensor Selection Method Based on Proximal Optimization for High-Dimensional Data With Correlated Measurement Noise
Takayuki Nagata, Keigo Yamada, Taku Nonomura +3
The present paper proposes a data-driven sensor selection method for a high-dimensional nondynamical system with strongly correlated measurement noise. The proposed method is based…
Randomized Group-Greedy Method for Large-Scale Sensor Selection Problems
Takayuki Nagata, Keigo Yamada, Kumi Nakai +2
The randomized group-greedy method and its customized method for large-scale sensor selection problems are proposed. The randomized greedy sensor selection algorithm is applied str…
Nondominated-Solution-based Multi-objective Greedy Sensor Selection for Optimal Design of Experiments
Kumi Nakai, Yasuo Sasaki, Takayuki Nagata +3
In this study, a nondominated-solution-based multi-objective greedy method is proposed and applied to a sensor selection problem based on the multiple indices of the optimal design…