School of Physical and Mathematical Sciences (SPMS)

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4,321 to 4,330 of 8,137 Results

theta = 20, phi = -10.tab Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications Tabular Data - 1000.8 KB - 340 Variables, 339 Observations - UNF:6:EK30gJefUqwbv/jo/IQ9pA== Required data for Figure 9.
theta = 25, phi = 50.tab Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications Tabular Data - 1000.3 KB - 340 Variables, 339 Observations - UNF:6:S8colQsykhGUDAgWGPlQxw== Required data for Figure 9.
theta = 25, phi = 95.csv Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications Comma Separated Values - 1003.8 KB - MD5: a22c3ebb53f165681a2ce4e468c746f2 Required data for Figure 9.
theta = 30, phi = 100.tab Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications Tabular Data - 1000.6 KB - 340 Variables, 339 Observations - UNF:6:zAHyTQahbK0ZjrT0z9FVaA== Required data for Figure 9.
transmission [f = 1 THz, p = 75 um, lz = 200 um].txt Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications Plain Text - 69.1 KB - MD5: faa231c9fce53e679dfe828df02c76d4 Required data for Figure 8.
twilight.m Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications MATLAB Source Code - 715 B - MD5: f0482d5c5e70b619d1cc2a6c0fb903c4 Matlab script: User-defined colormap
xN.txt Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications Plain Text - 335 B - MD5: 1205cd83a47bff913e7a988d0561055a Required data for Figure 9 and 10.
yM.txt Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications Plain Text - 335 B - MD5: 1205cd83a47bff913e7a988d0561055a Required data for Figure 9 and 10.
Replication Data for: Complex Patterns of Past and Ongoing Crustal Deformation in Southern California Revealed by Seismic Azimuthal Anisotropy Sep 2, 2022 - TONG Ping Tong, Ping, 2022, "Replication Data for: Complex Patterns of Past and Ongoing Crustal Deformation in Southern California Revealed by Seismic Azimuthal Anisotropy", https://doi.org/10.21979/N9/JQDOAQ, DR-NTU (Data), V2 Azimuthally anisotropic P-wave velocity model of the crustal structure beneath Southern California revealed by Adjoint-state Traveltime Tomography
Readme Sep 2, 2022 - Replication Data for: Complex Patterns of Past and Ongoing Crustal Deformation in Southern California Revealed by Seismic Azimuthal Anisotropy Plain Text - 756 B - MD5: 299a43e3d1dff0a6ff1471dd73bef344 Documentation

theta = 20, phi = -10.tab

Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Tabular Data - 1000.8 KB - 340 Variables, 339 Observations -

Required data for Figure 9.

theta = 25, phi = 50.tab

Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Tabular Data - 1000.3 KB - 340 Variables, 339 Observations -

Required data for Figure 9.

theta = 25, phi = 95.csv

Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Comma Separated Values - 1003.8 KB -

Required data for Figure 9.

theta = 30, phi = 100.tab

Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Tabular Data - 1000.6 KB - 340 Variables, 339 Observations -

Required data for Figure 9.

transmission [f = 1 THz, p = 75 um, lz = 200 um].txt

Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Plain Text - 69.1 KB -

Required data for Figure 8.

twilight.m

Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

MATLAB Source Code - 715 B -

Matlab script: User-defined colormap

xN.txt

Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Plain Text - 335 B -

Required data for Figure 9 and 10.

yM.txt

Sep 15, 2022 - Self-adaptive deep reinforcement learning for THz beamforming with silicon metasurfaces in 6G communications

Plain Text - 335 B -

Required data for Figure 9 and 10.

Replication Data for: Complex Patterns of Past and Ongoing Crustal Deformation in Southern California Revealed by Seismic Azimuthal Anisotropy

Sep 2, 2022 - TONG Ping

Tong, Ping, 2022, "Replication Data for: Complex Patterns of Past and Ongoing Crustal Deformation in Southern California Revealed by Seismic Azimuthal Anisotropy", https://doi.org/10.21979/N9/JQDOAQ, DR-NTU (Data), V2

Azimuthally anisotropic P-wave velocity model of the crustal structure beneath Southern California revealed by Adjoint-state Traveltime Tomography

Readme

Sep 2, 2022 - Replication Data for: Complex Patterns of Past and Ongoing Crustal Deformation in Southern California Revealed by Seismic Azimuthal Anisotropy

Plain Text - 756 B -

Documentation

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