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Record W2054274626 · doi:10.1109/mwscas.2010.5548572

Modifications of a Dynamic-Logic Phase Frequency Detector for extended detection range

2010· article· en· W2054274626 on OpenAlexafffund
Cheng Zhang, M. Syrzycki

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhase frequency detectorDetectorCMOSPhase differenceElectronic engineeringPhase detectorPhase (matter)Computer scienceRange (aeronautics)Phase-locked loopLinear phasePolarity (international relations)Electronic circuitDynamic rangeControl theory (sociology)EngineeringElectrical engineeringPhysicsPhase noiseTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents two modified architectures of a Dynamic-Logic Phase Frequency Detector (PFD) which eliminate the blind-zone problem. The PFDs have linear phase-frequency characteristics for the input phase difference outside of the blind-zone, and constant phase-frequency characteristics for the phase difference inside the blind-zone. The proposed new PFD architectures extend the detection range and eliminate the polarity reversal issue of the output. The circuits have been designed in 0.13 μm CMOS technology and the simulation results have demonstrated a detection range improvement in comparison to previously existing solutions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.646
Threshold uncertainty score0.294

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 head0.017
GPT teacher head0.291
Teacher spread0.274 · 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 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

Citations21
Published2010
Admission routes2
Has abstractyes

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