Form of presentation | Conference proceedings in Russian journals and collections |
Year of publication | 2015 |
Язык | английский |
|
Mosin Sergey Gennadevich, author
|
Bibliographic description in the original language |
Mosin, S. An Approach to Construction the Neuromorphic Classifier for Analog Fault Testing and Diagnosis, Proc. of 4th Mediterranean Conference on Embedded Computing (MECO), Budva, Montenegro – ISBN 978-1-4799-8999-7 |
Annotation |
Proc. of 4th Mediterranean Conference on Embed-ded Computing (MECO) |
Keywords |
Testing, diagnosis, neural network, classification, clusterization |
The name of the journal |
Proc. of 4th Mediterranean Conference on Embed-ded Computing (MECO)
|
URL |
http://dx.doi.org/10.1109/MECO.2015.7181917 |
Please use this ID to quote from or refer to the card |
https://repository.kpfu.ru/eng/?p_id=125502&p_lang=2 |
Full metadata record |
Field DC |
Value |
Language |
dc.contributor.author |
Mosin Sergey Gennadevich |
ru_RU |
dc.date.accessioned |
2015-01-01T00:00:00Z |
ru_RU |
dc.date.available |
2015-01-01T00:00:00Z |
ru_RU |
dc.date.issued |
2015 |
ru_RU |
dc.identifier.citation |
Mosin, S. An Approach to Construction the Neuromorphic Classifier for Analog Fault Testing and Diagnosis, Proc. of 4th Mediterranean Conference on Embedded Computing (MECO), Budva, Montenegro – ISBN 978-1-4799-8999-7 |
ru_RU |
dc.identifier.uri |
https://repository.kpfu.ru/eng/?p_id=125502&p_lang=2 |
ru_RU |
dc.description.abstract |
Proc. of 4th Mediterranean Conference on Embed-ded Computing (MECO) |
ru_RU |
dc.description.abstract |
Testing and diagnosis of analog circuits are very important tasks at the quality assurance of integrated circuits and electronic devices. Faults detection and identification are realized using fault dictionary. The architecture of fault dictionary has an essential influence on time and efficiency of diagnosis at whole. An approach to the construction of fault dictionary as the neuromorphic classifier for analog fault testing and diagnosis is proposed. The approach takes into account the component tolerances, includes the faults clustering as the preprocessing and selection the essential characteristics of CUT's output responses providing the maximum distinguishability between all fault clusters. The experimental results were obtained for second-order bandpass filter and are presented in the paper for demonstrating the proposed approach |
ru_RU |
dc.language.iso |
ru |
ru_RU |
dc.subject |
Testing |
ru_RU |
dc.subject |
diagnosis |
ru_RU |
dc.subject |
neural network |
ru_RU |
dc.subject |
classification |
ru_RU |
dc.subject |
clusterization |
ru_RU |
dc.title |
An Approach to Construction the Neuromorphic Classifier for Analog Fault Testing and Diagnosis |
ru_RU |
dc.type |
Conference proceedings in Russian journals and collections |
ru_RU |
|