174 | | - Created new numpy data table for regression model training (3 columns: RFI Scenario | Transmitting Signal Spectrogram | Brightness Temperature) |
175 | | - Since brightness temperatures of all samples from a single RFI scenario (band, central frequency, resource block, gain) are uniformly distributed, we ordered the Tb values obtained from the reference testbed L1B data from lowest to highest, and matched them with the 10 spectrograms generated with different marginalized signal gain values (uniform from -0.276 to +0.317) that simulate variation in physical transmission |
| 174 | - Created new numpy data table for regression model training |
| 175 | - (3 columns: RFI Scenario | Transmitting Signal Spectrogram | Brightness Temperature) |
| 176 | - Since Tb values of all samples from a single RFI scenario (band, fc, rb, gain) are uniformly distributed, we ordered the Tb values obtained from the reference testbed L1B data from lowest to highest, and matched them with the 10 spectrograms generated with different marginalized signal gain values (uniform from -0.276 to +0.317) that simulate variation in physical transmission |