A prototype implementation of a two-channel frequency-translating hybrid ADC
Bibliographic record
Abstract
In this paper, a proof-of-concept prototype of a two-channel frequency-translating hybrid (FTH) analog-to-digital converter (ADC) is implemented using off-the shelf components. The FTH structure is suitable for high-bandwidth ADCs. In this architecture, the wideband input signal is decomposed into smaller frequency subbands (channels). Each channel consists of a two-path system that frequency translates its input signal to baseband, lowpass filters each path signal using identical analog baseband filters, and samples and digitizes each path signal using identical baseband lower-speed ADC circuits. Unlike conventional parallel architectures, sampling is accomplished after splitting the signal into narrow baseband components alleviating the need for high-speed S/H circuitry. After digitizing the signal in each channel, the low-rate subband samples are upconverted back to their respective center frequencies, filtered, and recombined to reconstruct the digital representation of the original wideband input signal. The digital filters are optimized to minimize the reconstruction error. It is shown that the effects of many major analog non- idealities can be compensated in the digital domain.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".