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This paper introduces an improved spectrum sensing technique that exploits the existing information in the signals received from both electric power grids and wireless media to allow power line communication systems to monitor the spectrum occupancy/holes in the frequency band between 1.7 and 100 MHz. The applied procedure for implementing the proposed technique is organized in time-frequency mapping, selection and extraction of quanta, features extraction and selection, and detection. The attained results based on a measured data set show that the performance of techniques based on neural networks is far superior when compared to the techniques based on Bayes.

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