A fully digital timing recovery scheme using two samples per symbol
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Bibliographic record
Abstract
In this paper, a new symbol timing recovery scheme is presented for digital receiver. The proposed algorithm belongs to the category of feedforward recovery and consists of two stages-phase estimation and interpolation. The phase estimation is to detect the clock phase of the sampled signal, which indicates the deviation of the reference sample from the point of maximum eye-opening. The interpolation which is implemented with an FIR filter is to reconstruct the transmitted symbols. Although many estimation algorithms have been developed in the literature, these methods usually need an input sampling rate of at least four samples per symbol. The proposed scheme requires only two samples/symbol, thus allowing the use of a very low sampling rate at the receiver. This feature is very important in the implementation of a digital receiver for high-rate transmission, since the hardware cost of the receiver depends heavily on the required processing speed.
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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 | 0.001 | 0.002 |
| 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 it