Electromagnetic emissions were measured from several radio receivers to demonstrate the possibility of detecting and identifying these devices based on their unintended emissions. Radiated fields from the different radio receivers have unique characteristics that can be used to identify these devices by analyzing time-frequency plots of measured radiation. A neural network was also developed for automated device detection.
H. Weng et al., "Neural Network Detection and Identification of Electronic Devices Based on Their Unintended Emissions," Proceedings of the 2005 International Symposium on Electromagnetic Compatibility, 2005, Institute of Electrical and Electronics Engineers (IEEE), Jan 2005.
The definitive version is available at http://dx.doi.org/10.1109/ISEMC.2005.1513508
2005 International Symposium on Electromagnetic Compatibility, 2005
Electrical and Computer Engineering
Keywords and Phrases
Automated Device Detection; Electromagnetic Emissions; Electromagnetic Waves; Electronic Devices; Neural Nets; Neural Network Detection; Radio Receivers; Time-Frequency Plots; Unintended Emissions
Article - Conference proceedings
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