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Record W4233090067 · doi:10.36227/techrxiv.14067713

A Very Low-phase-noise CMOS Ring VCO Intended for Sensor Interfaces

2021· preprint· en· W4233090067 on OpenAlexfundno aff
Mahin Esmaeilzadeh, Yves Audet, Mohamed Ali, Mohamad Sawan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSemiconductor Lasers and Optical Devices
Canadian institutionsnot available
FundersMitacsCMC Microsystems
KeywordsVoltage-controlled oscillatorPhase noisedBcCMOSElectrical engineeringLinearityElectronic engineeringVoltageNoise (video)Offset (computer science)Materials scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

<p>We describe in the paper a ring voltage-controlled oscillator (VCO) indicating an improved phase noise over a wide range of frequency offsets and an extended frequency/voltage tuning range. The phase noise is improved by leveraging a better linearity approach, while reducing the VCO gain and maintaining wide tuning range. The proposed VCO is a block of a time-domain comparator embedded in a monitoring and readout circuit of an industrial sensor interface. An analytical model is extracted resulting in closed-form expressions for both input-referred noise and phase noise of the VCO. Employing the analytical expressions, the contributed noise and phase noise limitations are fully addressed, and all the effective factors are investigated. The prototype of the proposed VCO was implemented and fabricated in a 0.35 µm CMOS process. The integrated VCO consumes 0.903 mW from a 3.3 V supply, when running at its maximum frequency of 9.37 MHz. The measured phase noise of the proposed VCO is -147.57 dBc/Hz at 1 MHz offset from the 9.37 MHz oscillation frequency, and the occupied silicon area of circuit is 0.005 mm<sup>2</sup>.</p>

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 categoriesMeta-epidemiology (narrow)
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 score0.316
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.271
Teacher spread0.247 · 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
Published2021
Admission routes1
Has abstractyes

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