Spur Model for a Fixed-Frequency Signal Subject to Periodic Jitter
Bibliographic record
Abstract
This paper presents an automated algorithm that is capable of predicting both the location and magnitude of spurs that are caused by different sources of jitter on a periodic signal. A practical circuit that produces this kind of jittered periodic signal is the direct digital period synthesis (DDPS) circuit that can be used as a flexible clock source for various applications such as adjusting a sampling rate in a measurement and signal processing. Points of interest with clocks that are subject to periodic perturbations are their spectral purity and jitter characteristics. Our algorithm is applied to the DDPS to greatly reduce the simulation time that is needed to accurately compute the spectrum of the signal and its spurious frequency content. The method is used to explore how the operating parameters of the DDPS influence the spectral purity of its output. The generic analysis method that has been used in this paper can be transposed to fractional-Nsynthesizers, delay-line-based direct digital synthesizers, or serializers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".