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Jammer detection in M-QAM-OFDM by learning a Dynamic Bayesian Model for the Cognitive Radio.

, , , , , and . EUSIPCO, page 1-5. IEEE, (2019)

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AI-Based Abnormality Detection at the PHY-Layer of Cognitive Radio by Learning Generative Models., , , , , , and . IEEE Trans. Cogn. Commun. Netw., 6 (1): 21-34 (2020)Deep Learning for Spectrum Anomaly Detection in Cognitive mmWave Radios., , , , and . PIMRC, page 1-7. IEEE, (2020)Jammer detection in M-QAM-OFDM by learning a Dynamic Bayesian Model for the Cognitive Radio., , , , , and . EUSIPCO, page 1-5. IEEE, (2019)Active Inference Integrated With Imitation Learning for Autonomous Driving., , , , , and . IEEE Access, (2022)A Novel Resource Allocation for Anti-Jamming in Cognitive-UAVs: An Active Inference Approach., , , , and . IEEE Commun. Lett., 26 (10): 2272-2276 (2022)Automatic Jamming Signal Classification in Cognitive UAV Radios., , , , and . IEEE Trans. Veh. Technol., 71 (12): 12972-12988 (2022)Learning Self-Awareness Models for Physical Layer Security in Cognitive and AI-enabled Radios.. University of Genoa, Italy, (2022)base-search.net (ftunivgenova:oai:iris.unige.it:11567/1074612).Autonomous Driving Based on Imitation and Active Inference., , , , , and . SYSINT, volume 546 of Lecture Notes in Networks and Systems, page 13-22. Springer, (2022)Integrated Sensing and Communication for Joint GPS Spoofing and Jamming Detection in Vehicular V2X Networks., , , and . WCNC, page 1-7. IEEE, (2023)Incremental Learning through Probabilistic Behavior Prediction., , , , and . EUSIPCO, page 1502-1506. IEEE, (2022)