Sub-1 volt class AB amplifier with low noise, ultra low power, high-speed, using winner-take-all
Bibliographic record
Abstract
The proposed circuit utilizes a method to lower the output noise (Vonoise) of an amplifier by band-pass filtering it, while the amplifier's speed is increased by dynamically boosting its operating current when the amplifier's inputs (VIN) receive a large transient signal. This amplifier uses a winner-take-all (WTA) circuit that detects un-equilibrium at VIN, upon which the amplifier's bias current and its dynamic response are boosted. The WTA has a symmetric structure and operates in current mode that enhances the amplifier's dynamic response during boost on and off conditions, and facilitates operations at low power supply voltage (VDD). The boost signals that WTA initiates, feed a summing and floating current source (FCS) that also have a complementary and symmetric structure, which accommodates rail-to-rail (RR) dynamic biasing and improves VDDtransient and noise rejection. Monte Carlo (MC) and worst case (WC) simulations are performed, indicating the following specifications as attainable: large-signal settling time (ts) ∼ 1μs, current consumption (IDD) ∼ 85nA, VDDunder 1 volt (V), VONOISEat 1KHz ∼ 75μV/√Hz, gain (Av) ∼ 98dB, unity gain frequency (fu) ∼ 70kHz, phase margin (PM) ∼ 80 degrees, PSRR ∼ 115dB, CMRR ∼ 145dB. Amplifier rough area ∼ 45μm/side in 0.18μm CMOS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".