A Sample-Time Error Compensation Technique for Time-Interleaved ADC Systems
Bibliographic record
Abstract
Sample-time error among different channels of a time-interleaved analog-to-digital converter (ADC) is a factor in significant degradation of the ADC performance, especially in high frequencies. A two-channel, time-interleaved ADC structure with a background sample-time error compensation technique has been implemented. The sample-time error detection technique uses random data and has been implemented in the digital domain at a low level of complexity. The error correction is performed by adjusting the delay of the clock path of one channel, using a 6-bit digitally-controlled delay element (DCDE). At a sampling rate of 400 MSamples/s, the experimental results show that the spurious-free dynamic range (SFDR) of the ADC system is improved to 58.8 dB at 190 MHz. The ADC system achieves a signal-to-noise-and-distortion ratio (SNDR) of 59.6 dB at 5 MHz and 55.2 dB at 190 MHz after compensation. This error compensation method is especially suitable for time-interleaved ADCs used in digital data communication systems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".