Classification of PCB configurations from radiated EMI by using neural network
| Autor: | Y. Preampraneerach, K. Aunchaleevarapan, Werachet Khan-ngern, Shuichi Nitta, K. Paithoonwatanakij |
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| Rok vydání: | 2002 |
| Předmět: |
Engineering
Quantitative Biology::Neurons and Cognition Artificial neural network Physics::Instrumentation and Detectors business.industry Computer Science::Neural and Evolutionary Computation Process (computing) Hardware_PERFORMANCEANDRELIABILITY Electromagnetic interference Printed circuit board ComputingMethodologies_PATTERNRECOGNITION EMI Hardware_INTEGRATEDCIRCUITS Electronic engineering business Radiated emission Hardware_LOGICDESIGN |
| Zdroj: | Proceedings. Asia-Pacific Conference on Environmental Electromagnetics. CEEM'2000 (IEEE Cat. No.00EX402). |
| DOI: | 10.1109/ceem.2000.853911 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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