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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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OFDM Recognition Based on Cyclostationary Analysis in an Open Spectrum Scenario., , , and . VTC Spring, IEEE, (2009)Representation and Learning of Structured Dynamic Bayesian Models in Non Stationary Environments.. DCNET, page 5. SciTePress, (2017)A Cognitive Control-Inspired Approach to Object Tracking., , , and . IEEE Trans. Image Processing, 25 (6): 2697-2711 (2016)Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions., , , , and . Electronic Imaging: Image and Video Communications and Processing, volume 5685 of SPIE Proceedings, SPIE, (2005)Exploiting ST-Based Representation for High Sampling Rate Dynamic Signals., , , , and . WIDECOM, volume 27 of Lecture Notes on Data Engineering and Communications Technologies, page 203-217. Springer, (2019)Comparison among Cognitive Radio Architectures for Spectrum Sensing., , , and . EURASIP J. Wireless Comm. and Networking, (2011)Exploiting an event based state estimator in presence of sparse measurements in video analytics., , , and . ICASSP, page 1871-1875. IEEE, (2014)A post-processing algorithm for performance enhancement of remote video-based monitoring systems., , and . MMSP, page 351-356. IEEE, (1999)A particle filter based sequential trajectory classifier for behavior analysis in video surveillance., , and . ICIP, page 3690-3694. IEEE, (2015)Robust tracking of humans and vehicles in cluttered scenes with occlusions., , , and . ICIP (3), page 629-632. IEEE, (2002)