Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/15309
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Bajovic V. | en |
dc.contributor.author | Bojkovic G. | en |
dc.contributor.author | Kovacevic V. | en |
dc.date.accessioned | 2020-03-03T14:59:24Z | - |
dc.date.available | 2020-03-03T14:59:24Z | - |
dc.date.issued | 1997-01-01 | en |
dc.identifier.uri | https://open.uns.ac.rs/handle/123456789/15309 | - |
dc.description.abstract | A knowledge-based system is proposed and described for faulty components detection and identification, in production testing of analog electronic boards. Its main parts are: the guided measuring probe and diagnostic expert system. Results are reported of using inductive machine learning technique for diagnostic rules acquisition. | en |
dc.relation.ispartof | IEEE International Symposium on Electronics & the Environment | en |
dc.title | Knowledge based system for faulty components detection in production testing of electronic device | en |
dc.type | Conference Paper | en |
dc.identifier.scopus | 2-s2.0-0030698533 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/0030698533 | en |
dc.relation.lastpage | 260 | en |
dc.relation.firstpage | 257 | en |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
Appears in Collections: | Naučne i umetničke publikacije |
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