A low-cost ATE phase signal generation technique for test applications
Bibliographic record
Abstract
In this article, an accurate and low-cost clock delay generation system integrated in an automated test equipment (ATE) environment is presented. The input to this system is entirely digital and is driven by a single clock, which can be programmed from the ATE High Speed Digital (HSD) unit. Moreover, the digital input patterns can easily be generated in software off-line; hence, making this system ideal for automated test routines. The system is first discussed and characterized in Matlab under static and dynamic operating conditions. For the static behavior, the impact of the various design tradeoffs on the time resolution is investigated. With regards to the dynamic behavior, the linearity is assessed spectrally with a sinusoidal input and statistically using a Gaussian noise signal. A discrete prototype board is built to validate the correct operation of the system mounted on an ATE to function as a whole. With proper compensation and calibration, a delay resolution of 15 ps was achieved over an 8.4 ns range using a low-speed reference clock running at 16.67 MHz. It is shown through clock scaling that this resolution can improve in direct proportion to increases in the clock frequency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".