A Static Phase Offset Reduction Technique for Multiplying Delay-Locked Loop
Bibliographic record
Abstract
Static phase offset (SPO) in conventional multiplying delay-locked loops (MDLLs) dramatically degrades the deterministic jitter performance. To overcome the issue, this paper presents a new SPO reduction technique for MDLLs. The technique is based on the observation that the SPO of MDLL is mainly caused by the non-idealities on charge pump (e.g. sink and source current mismatch), and control line (e.g. gate leakage of loop filter and voltage controlled delay line (VCDL) control circuit). With a high gain stage inserting between phase detector/phase frequency detector (PD/PFD) and charge pump, the equivalent SPO has been decreased by a factor equal to the gain of the gain stage. The effectiveness of the proposed technique is validated by a Simulink model of MDLL. The equivalent SPO is measured by the power level of reference spur.
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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".