Data-driven approach for noise reduction in pressure-sensitive paint data based on modal expansion and time-series data at optimally placed points

Tomoki Inoue, Yu Matsuda, Tsubasa Ikami, Taku Nonomura, Yasuhiro Egami, Hiroki Nagai

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Fingerprint

Dive into the research topics of 'Data-driven approach for noise reduction in pressure-sensitive paint data based on modal expansion and time-series data at optimally placed points'. Together they form a unique fingerprint.

Mathematics

Physics & Astronomy

Engineering & Materials Science

Chemical Compounds