A 10-bit 110 kS/s 1.16 <inline-formula> <tex-math notation="TeX">$\mu\hbox{W}$</tex-math> </inline-formula> SA-ADC With a Hybrid Differential/Single-Ended DAC in 180-nm CMOS for Multichannel Biomedical Applications
Bibliographic record
Abstract
A 10-bit 110-kS/s successive-approximation analog-to-digital converter (ADC) for multichannel biomedical applications is presented. In order to achieve low-power operation, the ADC utilizes a reduced-speed dynamic comparator, a low-complexity calibration technique, a hybrid single/differential digital-to-analog converter architecture, and an attenuation capacitor with low sensitivity to mismatch errors. Fabricated in 180-nm CMOS, this ADC consumes a total power of 1.16 μW from 1.5 V/1.2 V analog/digital power supplies. The integral nonlinearity is between -1.23 LSB and 1.19 LSB, whereas the differential nonlinearity is between -0.71 LSB and 0.92 LSB. The ADC signal-to-noise-and-distortion ratio and spurious-free dynamic range are 56.1 and 67 dB with a 39.5-kHz sinusoid input, respectively. The ADC figure-of-merit is of 20 fJ per conversion step, which is very competitive, as compared with state-of-the-art ADCs in similar 180-nm CMOS technologies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".