A low-power, 5-70 MHz, 7th-order filter with programmable boost, group delay, and gain using instantaneous companding
Bibliographic record
Abstract
A seventh-order 0.05/spl deg/ equiripple linear-phase continuous-time filter employing, for the first time, instantaneous companding, was designed and integrated in a mature bipolar process. The amount of boost (up to 13 dB) and group-delay adjustment (30%) are digitally programmable. The DC gain is controllable up to 10 dB, and the -3 dB frequency (f/sub c/) is tunable from 5 to 70 MHz. The output swing for 1% TED is higher than 100m V/sub pp/, with a 1.5 V supply. The filter consumes very low power (5-13 mW for f/sub c/=70MHz) compared to conventional implementations (e.g. 120 mW for f/sub c/=100 MHz).
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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 | 0.000 | 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) | 0.000 | 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".