Frequency calibration of the system clock of passive wireless microsystems
Bibliographic record
Abstract
This thesis presents a theoretical and simulated study of frequency calibration of the system clock of passive wireless microsystems. The proposed frequency calibration technique achieves ultra-low power, high fre- quency accuracy, and fast calibration of the frequency of a local oscillator in a passive wireless microsystem using a frequency-locked loop (FLL). A new integrating frequency dif- ference detector (iFDD) that senses the frequency difference between the local oscillator and a reference clock is also proposed. The iFDD is implemented using a switched-capacitor network with two integrating paths. The FLL is composed of a logic-control block for gen- eration of clock signals, the iFDD, and a relaxation voltage-controlled oscillator. A detailed analysis of the characteristics of the iFDD in the time and frequency domains is presented. The loop dynamics of the FLL is also investigated. The proposed FLL is implemented in IBM 0.13-µm, 1.2 V CMOS technology and is validated through simulations using Spectre APS.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".