FUNABA, Hisamichi

No ORCID on file · 255 papers in corpus · active 2024-2025

Study types

  • dataset 255
dataset 2025
·doi:10.57451/lhd.a.thomson_add.191851.1

Thomson scattering data which are requested by users. For example, integrated signals of multiple laser pulses are used.

dataset 2025
·doi:10.57451/lhd.a.thomson_add.192326.1

Thomson scattering data which are requested by users. For example, integrated signals of multiple laser pulses are used.

dataset 2025
·doi:10.57451/lhd.a.thomson_add.97001.1

Thomson scattering data which are requested by users. For example, integrated signals of multiple laser pulses are used.

dataset 2025
·doi:10.57451/lhd.a.thomson_add.97123.1

Thomson scattering data which are requested by users. For example, integrated signals of multiple laser pulses are used.

dataset 2025
·doi:10.57451/lhd.thomsondc.112269.1

Pure raw signal data measured by avalanche photo diodes (APD) and pre-amplifires in Thomson scattering polychromators. Monitoring of the intensity of the plasma light incident on the APD surface.

dataset 2025
·doi:10.57451/lhd.thomsondc.89049.1

Pure raw signal data measured by avalanche photo diodes (APD) and pre-amplifires in Thomson scattering polychromators. Monitoring of the intensity of the plasma light incident on the APD surface.

dataset 2025
·doi:10.57451/lhd.thomsondc.96944.1

Pure raw signal data measured by avalanche photo diodes (APD) and pre-amplifires in Thomson scattering polychromators. Monitoring of the intensity of the plasma light incident on the APD surface.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.101244.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.102106.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.102601.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.103604.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.106242.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.110949.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.116776.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.119725.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.128145.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.132537.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.134600.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.136116.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.143635.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.144001.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.148542.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.153085.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.155865.1

Results of fitting using the neural network variational Bayesian method on Thomson data.

dataset 2025
·doi:10.57451/lhd.a.thomson_fit.159733.1

Results of fitting using the neural network variational Bayesian method on Thomson data.