A 3.04-fs FoM Hybrid LDO Regulator with Fast Transient Algorithm and Wide Load Range
Bibliographic record
Abstract
This paper presents a novel approach to fast response low clock frequency hybrid LDO. The proposed design uses charge distribution to estimate the size of power transistor required to achieve the correct output voltage. This method significantly reduces the amount of clock cycles to achieve a steady state. In conjunction with the proposed digital algorithm, an analog error amplifier is added to the system to achieve zero current capability as well as improved voltage regulation at low load currents. In presence of the analog-assisted loop, an inverter based droop detector is implemented to reduce the undershoot and further increase conversion speed. The proposed LDO is design in a TSMC 180-nm 1.8 V standard CMOS process and analyzed using Spectre with BSIM3 device models. Post-layout simulation confirms that with a 10 MHz clock, the LDO is capable of providing up to 120 mA at a stable 1.2 V output. A 1.17 μs transient response for a full range load step with a maximum droop voltage of 253 mV is obtained.
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 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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".