A hybrid phase-locked loop for CDR Applications
Bibliographic record
Abstract
In this paper, a hybrid phase and frequency detector (PFD) for phase-locked loop (PLL) based clock and data recovery (CDR) applications is presented. The PFD starts the phase detection process in a binary mode, for a faster acquisition time and a higher pull in range, and after the binary PLL locks, the PD switches to the linear mode of operation resulting in a lower output jitter. The frequency acquisition range of the presented PFD is significant and it virtually can handle any data frequency. The data frequency can however be as high as the clock frequency. In all simulations of the PLL, the pull-in range of the PLL is limited by the tuning range of the voltage-controlled oscillator (VCO). A prototype PLL is designed in a 0.13 µm CMOS technology and has a lock range from 8.3 to 9.6 GHz, peak-to-peak jitter of 0.1 UI, and a worst-case lock time of 30 ns. The PLL consumes 36 mW from a 1.2 V supply.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".