DocumentCode
3288804
Title
Data driven neural-based measurement discrimination for IC parametric faults diagnosis
Author
Wu, Angus ; Meador, Jack
Author_Institution
Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USA
fYear
1992
fDate
7-9 April 1992
Firstpage
194
Lastpage
197
Abstract
Describes experimental results obtained with the use of data driven neural-based system for statistical IC fault diagnosis. Measurement discrimination is established through a reduction method involving data pre-processing in a fashion consistent with a specific definition of parametric faults. The effects of this preprocessing are examined in the context of a realistic IC parametric fault diagnostic problem.<>
Keywords
automatic testing; fault location; feedforward neural nets; integrated circuit testing; IC parametric faults diagnosis; data driven neural-based system; data pre-processing; statistical IC fault diagnosis; Accuracy; Computer science; Electric variables measurement; Fault diagnosis; Frequency response; Lifting equipment; Logistics; Maximum likelihood estimation; Operational amplifiers; Transient response;
fLanguage
English
Publisher
ieee
Conference_Titel
VLSI Test Symposium, 1992. '10th Anniversary. Design, Test and Application: ASICs and Systems-on-a-Chip', Digest of Papers., 1992 IEEE
Conference_Location
Atlantic City, NJ, USA
Print_ISBN
0-7803-0623-6
Type
conf
DOI
10.1109/VTEST.1992.232748
Filename
232748
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