A novel double sampling technique for delta-sigma modulators
Bibliographic record
Abstract
The double sampling technique is used to achieve twice the sampling frequency in sampled-data systems without extra requirements (e.g., clock rate, op-amp settling time, op-amp dc gain, etc.). In this paper, theoretical analyses of the effects of nonidealities (integrator leakage, path gain mismatch and non-uniform sampling) on the performance of double sampling delta-sigma modulators (/spl Delta//spl Sigma/M's) are given. A novel double sampling technique for /spl Delta//spl Sigma/M's which is insensitive to the path gain mismatch is also presented. This technique uses a bilinear integrator in the first stage, resulting in a first order shaping of the path gain mismatch error. Compared with a second-order single sampling /spl Delta//spl Sigma/M, this technique is able to achieve 15 dB improvement of S/N and 6 dB relaxation of op-amp dc gain.
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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".