Field-programmable analog array implemented using delta-sigma based digital signal processing
Bibliographic record
Abstract
Field-Programmable Analog Arrays offer an ease of design, a fast turn-around time and low non-recurrent costs, but the noise inserted by the programmable circuits limits the resolution. This project implements the processing core of an FPAA using delta-sigma based digital signal processing, where the resolution is independent of the circuit noise. This digital FPAA allows the designer to trade off bandwidth for resolution, simplifies the programmable routing grid because all signals are 1-bit, and reduces the fabrication costs by using a low-cost digital CMOS process. The basic blocks of the FPAA can be programmed as a biquad filter, a sine wave oscillator or a 5-input mixer, which have a maximum SNR of 87.5dB with a bandwidth of 476kHz when operating at 244MHz. The FPAA, implemented in TSMC's 0.18μm CMOS technology, consumes 0.93W at full activity and occupies a core area of 6.28mm2. The speed of different full-adder cell architectures was also studied as part of this project.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".