Bibliographic record
Abstract
This study provides an in‐depth review of the principles, architectures and design techniques of CMOS time‐to‐digital converters (TDCs). The classification of TDCs is introduced. It is followed by the examination of the parameters quantifying the performance of TDCs. Sampling TDCs including direct‐counter TDCs, tapped delay‐line TDCs, pulse‐shrinking delay‐line TDCs, cyclic pulse‐shrinking TDCs, direct‐counter TDCs with interpolation, vernier TDCs, flash TDCs, successive approximation TDCs and pipelined TDCs are studied and their pros and cons are compared. Noise‐shaping TDCs that reduce in‐band noise below technology limit are investigated. These TDCs include gated ring oscillator TDCs, switched ring oscillator TDCs, relaxation oscillator TDCs, ΔΣ TDCs and MASH TDCs. The performance of sampling and noise‐shaping TDCs is compared. The direction of future research on TDCs is explored.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".