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Record W2545325326 · doi:10.1109/asscc.2007.4425722

A 3.3 GHz LC-based digitally controlled oscillator with 5kHz frequency resolution

2007· article· en· W2545325326 on OpenAlexafffund
Jingcheng Zhuang, Qingjin Du, Tad Kwasniewski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhase noiseCenter frequencyFrequency synthesizerFrequency offsetDigitally controlled oscillatorFrequency multiplierVariable-frequency oscillatorCMOS500 kHzVoltage-controlled oscillatorOffset (computer science)Radio spectrumFrequency bandFrequency modulationElectronic engineeringMaterials scienceElectrical engineeringOptoelectronicsComputer sciencePhase-locked loopRadio frequencyVoltageBandwidth (computing)EngineeringTelecommunicationsOrthogonal frequency-division multiplexingBand-pass filter

Abstract

fetched live from OpenAlex

This paper reports a LC-based digitally controlled oscillator (DCO) with an enhanced frequency resolution and an extended linear frequency tuning range. It has a center frequency of 3.3GHz and a frequency tuning range of 600MHz covered by 64 different frequency bands. Each frequency band has 2048 linear tuning levels with a frequency step of 5kHz. This DCO was implemented in 90nm CMOS and the measured frequency tuning characteristics are provided in this paper. The DCO exhibits a phase noise of −118dBc/Hz at 1MHz frequency offset. The DCO core consumes 2mA current from 1.2V supply.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.006
GPT teacher head0.203
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), 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

Citations23
Published2007
Admission routes2
Has abstractyes

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Same topicAdvancements in PLL and VCO TechnologiesFrench-language works237,207