A new approach to the design of bilinear-LDI switched-capacitor filters having low passband sensitivity
Bibliographic record
Abstract
An approach to the design of low-sensitivity switched-capacitor (SC) filter is described. In this approach, the continuous-time reference transfer function is decomposed into a sum of two individual functions, and each function is realized as the transfer function of a voltage-divider network consisting of a resistance as its series arm and a reactive impedance as its shunt arm. The bilinear-LDI (lossless discrete integrator) design technique is applied to the SC realization of the two voltage-divider networks. These individual realizations are combined to form the SC realization of the overall filter. The resulting filter requires n+1 operational amplifiers (OAs) for its realization, where n is the order of the reference transfer function. For illustration purposes, the proposed approach is applied to the bilinear-LDI SC design of a practical sixth-order elliptic bandpass filter. It is shown that the filter exhibits low sensitivity to dominant-pole OA effects.>
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".