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Mostrar el registro sencillo del ítem 2008-05-13T18:25:32Z 2008-05-13T03:00:00Z 2006-04
dc.description.abstract In this paper, we propose an efficient diagnosis scheme to detect and locate the switching network defects/faults in reconfigurable array architecture. This diagnosis scheme performs the test of switching network based on the scan path and fault intersection test methodology to locate the faults occurring in the switching network. After the diagnosis of switching network, the processing element (PE) test can then be initiated through the good switches and links. Errors in testing that cause a good switch, link or PE to be considered as a bad one is called "killing error". The issue of killing error in testing is addressed and the probability of killing error for our diagnosis technique is analyzed and shown to be extremely low. The significance of this approach is the ability to detect and locate the multiple faults in switches, links, and PEs with low testing circuit overhead, and to offer the good test quality in linear diagnosis time. en
dc.format.extent p. 12-21 es
dc.language en es
dc.title A Fault Diagnosis Scheme and Its Quality Issue in Reconfigurable Array Architecture en
dc.type Articulo es
sedici.identifier.uri es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Chen, Yung-Yuan es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.other switching network en
sedici.description.fulltext true es Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000000548 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 6, no. 1 es
sedici.subject.acmcss98 Reliability, Testing, and Fault-Tolerance es
sedici.subject.acmcss98 Arrays es

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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)