Oversampling A/D Converters With Reduced Sensitivity to DAC Nonlinearities
Bibliographic record
Abstract
To alleviate the image-rejection requirements of the front-end filters and the feedback digital-to-analog converter (DAC) matching requirements, an oversampling complex discrete-time (DT) DeltaSigma analog-to-digital converter (ADC) with a signal-transfer function that achieves significant filtering of interfering signals is proposed. With a filtering signal transfer function (STF) and stopband attenuation greater than 30 dB, the DeltaSigma modulator reduces the intermodulation of the desired signal and the interfering signals at the input of a quantizer, and also avoids feedback of high-frequency interfering signals at the input of the modulator. This filtering of the interfering signals reduces sensitivity to DAC nonlinearities. The reported DT complex DeltaSigma ADC is intended for digital television (DTV) receiver applications. With a maximum intended sampling frequency of 128 MHz and an oversampling ratio of 16, the ADC has been designed to support a maximum DTV signal bandwidth of 8 MHz. The IC achieved a 70.9-dB signal-to-noise-and-distortion ratio over a 6-MHz band centered around 3 MHz. The image-rejection ratio of the DeltaSigma ADC was measured to be greater than 65 dB. The fabricated chip consumes 122.4 mW and occupies a silicon area of 2.15 mm2.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".