MétaCan
Menu
Back to cohort
Record W2096562543 · doi:10.1109/icecs.2007.4511217

Signal Integrity Analysis of a High Precision D/A Converter

2007· article· en· W2096562543 on OpenAlexafffund
Olivier Valorge, D. Marche, Alain Lacourse, Mohamad Sawan, Yvon Savaria

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsSafe Engineering Services & Technologies (Canada)Polytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsGlitchRingingNoise (video)Current sourceElectronic engineeringCMOSCoupling (piping)Time domainElectrical engineeringSignal integrityVoltageSpicePower (physics)Computer sciencePhysicsEngineeringFilter (signal processing)Printed circuit board

Abstract

fetched live from OpenAlex

The purpose of this paper is to investigate the significance of different coupling mechanisms that occur in a high precision D/A converter. The standard Integrated Circuit Emission Model approach is applied to an existing D/A converter built in TSMC CMOS 0.25 μm technology. Aggressors, propagation media and victims are defined and modelled using classical CAD tools. Potential noise sources and victims are identified and some frequency and time domain simulation results reveal the noise source signatures. This study highlights the main noise source in such kind of converters: the charging/discharging switch current that occur at each sampling period. Based on detailed simulations, the 60 mV peak to peak voltage glitch observed on the output is explained by power and ground ringing due to current switches, whereas previous studies suggested that such glitches were due to substrate coupling. The simulated substrate propagated digital glitches have a peak to peak voltage of 5 mV, and are more than ten times lower than glitches induced by the current switch activities.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.007
GPT teacher head0.236
Teacher spread0.229 · 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 designBench or experimental
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

Citations0
Published2007
Admission routes2
Has abstractyes

Explore more

Same topicElectrostatic Discharge in ElectronicsFrench-language works237,207