A SigmaDelta modulator for digital hearing instruments using 0.18 mum CMOS technology.
Bibliographic record
Abstract
This thesis develops the design methodology for a low-voltage low-power SigmaDelta Modulator, realized using a switched op-amp technique that can be used in a hearing instrument. Switched op-amp implementation allows scaling down the design to the latest CMOS technology. A single-loop second-order SigmaDelta Modulator topology is chosen. The modulator circuit features reduced complexity, area reduction and low conversion energy. The modulator has a sampling rate of 8.2 MHz with an over-sampling ratio (OSR) of 256 to provide an audio bandwidth of 16 kHz. The modulator is implemented in a 0.18 mum digital CMOS technology with metal-to-metal sandwich structure capacitors. The modulator operates with a supply voltage of 1.8 V. The active area is 0.403 mm2. The modulator achieves a 98 dB signal-to-noise-and-distortion ratio (SNDR) and a 100 dB dynamic range (DR) at a Nyquist conversion rate of 32 kHz and consumes 1321 muW with a joule/conversion figure of merit equal to 161 x 10-12 J/s. The design methodology is developed through the extensive use of simulation tools. The behaviour simulation is carried out using Matlab/SIMULINK while circuits are simulated with Hspice using the Cadence design tools. Full-custom layout for the analog and the digital circuits is performed using the Cadence design tool. Post-processing simulation of the extracted modulator with parasitic verifies that results meet the requirements. The design has been sent to CMC for fabrication. Source: Masters Abstracts International, Volume: 43-03, page: 0947. Adviser: W. C. Miller. Thesis (M.A.Sc.)--University of Windsor (Canada), 2004.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".