Small-area decimators for delta-sigma video sensors
Bibliographic record
Abstract
A delta-sigma, or sigma-delta, analog-to-digital converter (ADC) comprises both a modulator, which implements oversampling and noise shaping, and a decimator, which implements low-pass filtering and downsampling. Whereas these ADCs are ubiquitous in audio applications, their usage in video applications is emerging. Because of oversampling, it is preferable to integrate delta-sigma ADCs at the pixel level of megapixel video sensors. Moreover, with pixel-level applications, area usage per ADC is much more important than with chip-level applications, where there is only one or a few ADCs per chip. Recently, a small-area decimator was presented that is suitable for pixel-level applications. However, though the pixel-level design is small enough for invisible-band video sensors, it is too large for visible-band ones. As shown here, nanoscale CMOS processes offer a solution to this problem. Given constant specifications, small-area decimators are designed, simulated, and laid out, full custom, for 180, 130, and 65nm standard CMOS processes. Area usage of the whole decimator is analyzed to establish a roadmap for the design and demonstrate that it could be competitive compared to other digital pixel sensors, based on Nyquist-rate ADCs, that are being commercialized.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".