Design of a 5-Bit Current Steering DAC for Driving High Forward Voltage LEDs
Bibliographic record
Abstract
Over past decades, light-emitting diodes (LEDs) have been identified as an ordinary part of many industrial and biomedical applications and many attempts done to enlarge their versatility. This paper proposes a 5-bit current steering DAC with the capability of driving two LEDs in a commercial OSRAM photoplethysmography (PPG) sensor which have different forward voltages. The DAC operates based on the thermometer-code conversion and is designed for 65 nm TSMC technology. Combined with a LED driver circuit it is able to convert a 5-bit digital input to an LED current signal. Results indicate that the implemented DAC can reach up to 50 M samples per second (MS/s) and changing its input by 1 LSB leads to 940 µA variation in the LED current. It is shown that the DAC system can independently drive two LEDs with the forward voltages of 1.8 V and 2.8 V at different time instants. According to the binary input signal of the DAC, the amplitude of the driving current signal, which identifies the brightness of LEDs, can be varied between 3.29 mA and 32.45 mA at a maximum frequency of 50 KS/s.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".