A High Bandwidth-Power Efficiency, Low THD2,3 Driver Amplifier with Dual-Loop Active Frequency Compensation for High-Speed Applications
Bibliographic record
Abstract
This paper presents a driver amplifier with high bandwidth-power efficiency, high capacitor-driving capacity, and low total harmonic distortion (THD). One complementary differential pair composed of self-cascode transistors is incorporated to obtain a full input voltage swing. Flipped voltage follower (FVF) buffers are applied as second stage to drive the last class-AB output stage. Moreover, a dual-loop active-feedback frequency compensation (DLAFC) is presented, which can stabilize the proposed multistage amplifier and keep the dominant pole on high frequency to obtain high-frequency total harmonic distortion (THD) suppression. To achieve a low-frequency phase margin protection (PMP), one left half-plane (LHP) zero is introduced to compensate for the nondominant pole caused by the load capacitor. Meanwhile, two high-frequency LHP zeros are injected to achieve high-frequency phase margin boosting (PMB) and reduce the amplifier’s settling time and integration area. This proposed amplifier is implemented in a standard DBH 0.18 μm 5 V CMOS process, and it achieves over 115-dB DC gain, 150–300 MHz GBW under 0–100 p load capacitors, ultra-high THD2,3 suppression ranges from 100 kHz to 10 MHz under 1–2 V output swing, and over 250 V/μs average slew rate, by only dissipating 12.5 mW at 5 V power supply.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".