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We present a study of power spectral density (PSD) estimation from data sampled in the time domain. This work was motivated by our recent development of digital
Ameya Ramadurgakar, Jake Rezac, Lennart Heijnen, Kate Remley, Dylan Williams, MELINDA PIKET-MAY, Rob Horansky
We introduce a type of RF fingerprint for nondestructive, cellular device identification. The new fingerprinting algorithm, termed Eigenphones, is a data-driven
Ameya Ramadurgakar, Kate Remley, Dylan Williams, Jake Rezac, MELINDA PIKET-MAY, Rob Horansky
Standard formulations of error vector magnitude compare a wireless device's symbol constellation to an ideal reference constellation. In this work, we utilize
Jason Killgore, Thomas Kolibaba, Benjamin Caplins, Callie Higgins, Jake Rezac
Machine learning models such as U-nets like the pix2pix conditional generative adversarial network (cGAN) are shown to predict 3D printed voxel geometry in
Dan Kuester, Xifeng Lu, Dazhen Gu, Azizollah Kord, Jake Rezac, Katie Carson, Marla L. Dowell, Elizabeth Eyeson, Ari Feldman, Keith Forsyth, Vu Le, John Marts, Mike McNulty, Kyle Neubarth, Andre Rosete, Matthew Ryan, Maija Teraslina
During the COVID-19 pandemic, NIST began a targeted campaign of measurements of averaged power and occupancy rate in the radio spectrum. The purpose was to