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• W2565573282 abstract "Analog circuits contribute to as much test cost as digital circuits. Traditional model-based testing (e.g. catastrophic, range-based, regression models) had limited success due to diversity of circuits and contributing metrics. We propose a model-free analog circuit testing using a combination of advanced signal processing and machine learning techniques with low computation and memory requirements. These unique features make the proposed test methodology scalable, reusable and suitable for both off-chip and on-chip test possibilities." @default.
• W2565573282 created "2017-01-06" @default.
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• W2565573282 date "2016-11-01" @default.
• W2565573282 modified "2023-09-22" @default.
• W2565573282 title "Model-Free Testing of Analog Circuits" @default.
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• W2565573282 doi "https://doi.org/10.1109/ats.2016.19" @default.
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