Built-in-test for integrating analog-to-digital converters that utilize a phase-sensitive detector
Bibliographic record
Abstract
Integrating analog-to-digital converters that utilize a phase-sensitive detector (PSADCs) are frequently used in high precision instrumentation and measurement systems. As any technical object, a PSADC is subject to faults. These faults must be detected promptly and accurately by built-in low complexity hardware. In the present work, this objective is achieved by the adoption of error-control codes. Off-line and on-line test methods are explored. We demonstrate how to perform compaction in digital and analog domains. We design a compactor of analog signals on the basis of a PSADC and explain how to utilize coding redundancy for on-line testing. We also explain how to use a PSADC for generating multiple residues which can further be processed by a computing device operating in a residue number system (RNS). Compared to existing techniques, the proposed approach is characterized by higher accuracy and lower latency. The proposed device can be used for analog circuits testing in much the same way as a conventional signature analyzer is used for digital circuits testing. The test process involves measuring signatures of analog signals, which ultimately appear in digital form. The signatures are then verified to make a pass/fail decision.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".