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Record W2177363184 · doi:10.1109/tcsii.2015.2468914

A 0.009–1.4-GHz Frequency Synthesizer With Suppressed Transients During VCO Band Switching

2015· article· en· W2177363184 on OpenAlexaff
Jerry Lam, Tom A. D. Riley, N.M. Filiol, John Rogers, Calvin Plett

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsVoltage-controlled oscillatorFrequency synthesizerPhase noiseCapacitorElectrical engineeringJitterDirect digital synthesizerPhase-locked loopVoltageCapacitanceMaterials sciencePhysicsElectronic engineeringEngineeringElectrode

Abstract

fetched live from OpenAlex

This brief presents a 0.009-1.4-GHz frequency synthesizer that is able to compensate for changes in the frequency tuning range, due to temperature variations, by switching voltage-controlled oscillator (VCO) bands with minimal phase and frequency errors, without cycle slipping and without introducing any phase offsets. This is accomplished by a subthreshold capacitor bank switching circuit that causes the gradual addition of capacitance slowly enough to allow the loop to adjust the VCO control voltage to compensate. The additional circuitry uses less than 0.001 mm2of silicon area and has minimal power consumption and minimal effects on the synthesizer's phase noise when fully switched. The synthesizer used to demonstrate this was implemented in a 0.18-μm SiGe BiCMOS process and achieves 365-fs integrated jitter at 1.05 GHz, with a total power consumption of 81 mW. Measurements of the capacitor bank switching circuit shows that it prevents cycle slipping during band switching and reduces the maximum frequency deviation by 99.3%.

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)0.001
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.208
Teacher spread0.190 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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