Bibliographic record
Abstract
Advances in technology and the introduction of high speed processors have increased the demand for fast, compact and commercial methods for transferring large amounts of data. The next generation of the communication access network will use optical fiber as a media for data transmission to the subscriber. In optical data or chip-to-chip data communication, the continuous received data needs to be converted to discrete data. For the conversion, a synchronous clock and data are required. A clock and data recovery (CDR) circuit recovers the phase information from the data and generates the in-phase clock and data. \nIn this dissertation, two clock and data recovery circuits for Giga-bits per second (Gbps) serial data communication are designed and fabricated in 180nm and 90nm CMOS technology. The primary objective was to reduce the circuit power dissipation for multi-channel data communication applications. The power saving is achieved using low swing voltage signaling scheme. Furthermore, a novel low input swing Alexander phase detector is introduced. The proposed phase detector reduces the power consumption at the transmitter and receiver blocks. \nThe circuit demonstrates a low power dissipation of 340µW/Gbps in 90nm CMOS technology. The CDR is able to recover the input signal swing of 35mVp. The peak-to-peak jitter is 21ps and RMS jitter is 2.5ps. Total core area excluding pads is approximately 0.01mm2.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.009 | 0.003 |
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".