Comparison of Bandpass $\Sigma\Delta$ Modulator Coding Efficiency With a Periodic Signal Model
Bibliographic record
Abstract
Maximizing coding efficiency is important in applications where bandpass SigmaDelta modulation is used as a source encoder to synthesize a two-level pulse train in RF class-D amplifiers. A periodic pulse-train model is developed to MIMIC the encoding of a bandpass SigmaDelta modulator for sinusoidal source signals, and it is shown that the coding efficiency of both the model and the modulator vary similarly with changes in carrier oversample ratio. The relationship between coding efficiency and carrier oversample ratio is not monotonic and has significant dips at certain ratios. The predictions of the model are compared with simulation results for a fourth-order bandpass modulator. The results show that coding efficiency is low in a modulator design where the input frequency is one-fourth the sample rate (f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ) and can be increased by as much as 15% by selecting a slightly lower oversample ratio such as (3/10)f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> .
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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) | 0.001 | 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".