: Isolates characteristics in the time and frequency domains (using Short-Time Fourier Transform) to distinguish harmful signals from useful data. 🧪 Scientific & Technical Applications
: Uses deep learning (like YOLOv8 or CNNs) to recognize interference types such as frequency hopping, sweeping, or single-frequency interference. InterferenceHD
: Precisely predicts the start/stop time and frequency range of a disruption, often with errors under 4ms or 6KHz. : Isolates characteristics in the time and frequency