A background calibration technique for multibit/stage pipelined and time-interleaved ADCs
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Bibliographic record
Abstract
A digital background calibration technique to compensate for the nonlinearity and gain error in the sub-digital-to-analog converter (SDAC), and the operational amplifier finite dc gain in multibit/stage pipelined analog-to-digital converter (ADC) is proposed. By injecting subtractive calibration voltages in a modified conventional multibit multiplying DAC and performing correlation based successive coefficient measurements, a background calibration is performed. This calibration technique does not need an accurate reference voltage or an increasing in the SDAC resolution. A global gain correction essential for time-interleaved ADCs is presented. Simulation results show that in the presence of realistic capacitor and resistance mismatch and finite op-amp gain, this technique improves the linearity by several bits in single and multi-channel pipelined ADC
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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 | 0.001 |
| 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