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| Content Provider | ACM Digital Library |
|---|---|
| Author | Biswas, Sounil Li, Peng Blanton, R. D. Shawn Pileggi, Larry T. |
| Abstract | Testing a non-digital integrated system against all of its specifications can be quite expensive due to the elaborate test application and measurement setup required.We propose to eliminate redundant tests by employing ¿-SVM based statistical learning.Application of the proposed methodology to an operational amplifier and a MEMS accelerometer reveal that redundant tests can be statistically identified from a complete set of specification-based tests with negligible error. Specifically, after eliminating five of eleven specification-based tests for an operational amplifier, the defect escape and yield loss is small at 0.6% and 0.9%, respectively.For the accelerometer, defect escape of 0.2% and yield loss of 0.1% occurs when the hot and colt tests are eliminated.For the accelerometer, this level of Compaction would reduce test cost by more than half. |
| Starting Page | 164 |
| Ending Page | 169 |
| Page Count | 6 |
| File Format | |
| ISBN | 0769522882 |
| ISSN | 15301591 |
| DOI | 10.1109/DATE.2005.277 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2005-03-07 |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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