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Record W1586764458

Analog-to-digital converter for input voltage measurements in low-power digitally controlled switch-mode power supply converters

2011· article· en· W1586764458 on OpenAlexaff
Aleksandar Radić, S. M. Ahsanuzzaman, Amir Parayandeh, Aleksandar Prodić

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBuck converterConvertersIntegrating ADCVoltageElectronic engineeringComputer scienceAnalog-to-digital converterSwitched-mode power supplyVoltage referencePower (physics)Buck–boost converterElectrical engineeringBoost converterEngineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper introduces a practical analog-to-digital (ADC) converter architecture for the input voltage measurements in low-power digitally controlled switch-mode power supplies (SMPS). The ADC utilizes known reference voltage and a duty ratio of a simple circuit mimicking operation of the converter to obtain the information about the input voltage value. The functionality of the ADC is verified through a discrete implementation, with a 1.5 V/3 W buck converter based experimental prototype. A better than 1.5% accuracy is observed over the entire 1.8 V to 3.3 V input voltage range. A small silicon size of about 0.025mm2 is also estimated, based on the synthesized digital logic and already existing on-chip integrated system functional blocks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.022
GPT teacher head0.214
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2011
Admission routes1
Has abstractyes

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