Impact of Noise on Trim Circuits for Bandgap Voltage References
Bibliographic record
Abstract
Mismatch and noise may impact the performance of integrated Bandgap voltage references. A usual solution to mitigate the impact of mismatch on performance is to include a trim circuit in the design. This technique results in more die area and longer test times. If the trim range is reduced, area and test time may be saved. Other factor that may also limit the performance of BGR circuits is the output noise, generated by integrated devices or from the supply voltage. Therefore, it is necessary to study how the output noise and variability due to process variations impact the design and applicability of trim circuits. Three BGR's were designed in a commercial 0.35 μm CMOS technology, and its trim range and noise performance evaluated. Results show that in high-order BGRs, where the output noise is more relevant, the output noise must be properly accounted for in the design of the BGR and trim circuit. Simultaneous analysis of noise and mismatch leads to reduced trim range and proper prediction of the maximum precision that can be achieved.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".