Delay‐compensation block for first‐order low‐pass delta‐sigma modulators
Bibliographic record
Abstract
Abstract Implementing the Delta Sigma Modulator (DSM) processing blocks on hardware is challenging due to the additional tap delays required by the digital processing blocks to process and output the result. The tap‐delays, known as latency, are necessary for the Field Programmable Gate Array (FPGA) operation to allow the logic gates to process the data at a given clock rate. These latencies alter the transfer function of the first‐order DSM as they present additional tap‐delays to the inherent delays within the DSM loop. A compensation block for the first‐order DSM is proposed to cancel‐out the effect of these latencies. By studying the transfer function, a combination of delays able to reconstruct the correct transfer function is determined. The solution was implemented on FPGA and tested using a 2.5 MHz signal. The post‐compensated DSM achieved a Signal‐to‐Noise‐and‐Distortion Ratio (SNDR) = 42 dB and an Adjacent Channel Leakage Ratio (ACLR) = 39 dB.
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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".