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Neural Network Approach to the Estimation of Radiated Emissions from Printed Circuit Boards

Neural Network (NN) and K-means clustering algorithm are used to detect the radiated emission's distribution in printed circuit boards (PCB). The self-organizing map (SOM) network is used for the first layer training. The SOM output data are clustered for the second time by K-means. The elbow method is used as the standard to judge the number of clusters in the final result. The simulation results can show the distribution of PCB radiation sources.