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Record W2178800835 · doi:10.1109/newcas.2011.5981288

Dynamic range scaling of sigma-delta modulators based on a multi-criteria optimization process

2011· article· en· W2178800835 on OpenAlexaff
Etienne Collard-Fréchette, Georges Kaddoum, Ghyslain Gagnon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsIntegratorCapacitorControl theory (sociology)ScalingVoltageDynamic rangeComputer scienceSwingDelta-sigma modulationNoise (video)Electronic engineeringMathematicsPhysicsEngineeringElectrical engineeringBandwidth (computing)Telecommunications

Abstract

fetched live from OpenAlex

This paper presents a new coefficient scaling technique to determine the dynamic range of the integrators of sigma delta modulators. This technique relies on numerical optimization of the interstage coefficients to minimize a multi-criteria objective function taking into account the sum of capacitor values implementing the modulator and the voltage swing at each integrator output, for a given target SNR. The optimization process includes the effect of thermal noise at each integrator stage. A user-defined parameter can steer the optimization process priority towards either the size of the capacitors or the integrators output voltage swing, depending on the given application.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.235
Teacher spread0.211 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2011
Admission routes1
Has abstractyes

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