Decision Feedback Equalizer Architectures With Multiple Continuous-Time Infinite Impulse Response Filters
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Bibliographic record
Abstract
Decision feedback equalizer (DFE) architectures with varying numbers of discrete-time taps and continuous-time infinite impulse response (IIR) filters are compared for use in typical wireline channels. In each case, the DFE coefficients are optimized to minimize a cost function that equally weights both jitter and vertical eye opening. Even when some reflections are present (e.g., backplane channels) continuous-time IIR taps can be effective if their filter coefficients are properly optimized. Using a DFE architecture with only two IIR filters provides adequate results for both a 26-dB loss coax cable and a 16" FR-4 backplane channel at 10 Gb/s while keeping the DFE complexity low. Furthermore, the implementation and experimental results of a DFE with multiple (three) IIR filters is reported. Fabricated in a 0.13 μm CMOS process, the DFE consumes 17.3 mW from a 1.2 V supply. A bit error rate (BER) of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-12</sup> was achieved at a data rate of 3.7 Gb/s.
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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) | 0.001 | 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 | 0.001 |
| 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 it