DocumentCode
2183886
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
fYear
2000
fDate
2000
Firstpage
105
Lastpage
110
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Environmental Electromagnetics, 2000. CEEM 2000. Proceedings. Asia-Pacific Conference on
Conference_Location
Shanghai
Print_ISBN
7-5635-0420-6
Type
conf
DOI
10.1109/CEEM.2000.853911
Filename
853911
Link To Document