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Cognitive RF systems use AI and machine learning to counter mode-agile emitters that evade traditional static threat libraries. The architecture includes RF acquisition, AI-driven analysis, waveform synthesis, and RF generation. Closed-loop testbeds with hardware-in-the-loop and system-in-the-loop testing iteratively develop and validate the AI/ML algorithms.
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