Dual-Path and Dual-Chopper Amplifier Signal Conditioning Circuit With Improved SNR and Ultra-Low Power Consumption for MEMS
Bibliographic record
Abstract
A dual chopper amplifier (DCA) signal conditioning circuit with ultra-low power consumption is presented for microelectromechanical systems transducers. In the first stage, a low voltage high current amplifier is implemented, which improves the power consumption and noise floor. The second stage is composed of two parallel paths that improve SNR and provide two gain settings. To mitigate flicker noise, the amplifiers are chopped at two different frequencies, also providing an additional degree of freedom to the design. The circuit is designed in a 0.13 μm CMOS technology with 0.7 and 1.2 V supplies. The power consumption is of 2.66 μW at the 0.7 V supply and 3.26 μW at the 1.2 V supply. For a 1.6 mV input, in single path mode, the DCA has a gain of 34 dB, a bandwidth of 4 kHz and achieves an SNR of 89.06 dB in the frequency range of 0.5-4 kHz. In dual path mode, the DCA has a gain of 38 dB, a bandwidth of 3 kHz and achieves an SNR of 92.85 dB in the frequency range of 0.5-4 kHz. The effect of the chopper at the second amplifier in the single path and dual path modes is detailed.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".