Title :
Classification of PCB configurations from radiated EMI by using neural network
Author :
Aunchaleevarapan, K. ; Khan-ngern, Werachet ; Nitta, Satya
Author_Institution :
Fac. of Eng., King Mongkut´s Inst. of Technol., Bangkok
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
Keywords :
circuit analysis computing; electromagnetic interference; learning (artificial intelligence); neural nets; pattern classification; printed circuits; PCB configurations classification; learning process; neural network; printed circuit board; radiated EMI; radiated emission spectra; training data; Algorithm design and analysis; Computer networks; Electromagnetic interference; Frequency; Neural networks; Pattern analysis; Printed circuits; Shape; Temperature measurement; Testing;
Conference_Titel :
Environmental Electromagnetics, 2000. CEEM 2000. Proceedings. Asia-Pacific Conference on
Conference_Location :
Shanghai
Print_ISBN :
7-5635-0420-6
DOI :
10.1109/CEEM.2000.853911
