The nature of statistical learning theory
The nature of statistical learning theory
Proceedings of the 40th annual Design Automation Conference
Multi-Modal Built-In Self-Test for Symmetric Microsystems
VTS '04 Proceedings of the 22nd IEEE VLSI Test Symposium
On path-based learning and its applications in delay test and diagnosis
Proceedings of the 41st annual Design Automation Conference
Support vector machine learning for interdependent and structured output spaces
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Statistical Test Compaction Using Binary Decision Trees
IEEE Design & Test
Adaptive test elimination for analog/RF circuits
Proceedings of the 46th Annual Design Automation Conference
On Boosting the Accuracy of Non-RF to RF Correlation-Based Specification Test Compaction
Journal of Electronic Testing: Theory and Applications
RF specification test compaction using learning machines
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Test-data volume optimization for diagnosis
Proceedings of the 49th Annual Design Automation Conference
Electrical calibration of spring-mass MEMS capacitive accelerometers
Proceedings of the Conference on Design, Automation and Test in Europe
Multidimensional analog test metrics estimation using extreme value theory and statistical blockade
Proceedings of the 50th Annual Design Automation Conference
Reducing test cost of integrated, heterogeneous systems using pass-fail test data analysis
ACM Transactions on Design Automation of Electronic Systems (TODAES)
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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 驴-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.