Classification of PCB configurations from radiated EMI by using neural network

Abstract

This paper presents a method of classifications of printed circuit board (PCB) with having several configuration by using neural network to recognized its spectrum. The learning process is accomplished by giving the neural network the different radiated emission spectra of 22 PCB configurations. The trained neural network is successfully able to predict the PCB configurations.