MétaCan
Menu
Back to cohort
Record W4234955442 · doi:10.22215/etd/2017-12225

A Fully Synthesized Injection Locked Ring Oscillator Based on a Pulse Injection Locking Technique

2017· dissertation· en· W4234955442 on OpenAlexaff
Mingze Li

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsInjection lockingdBcRing oscillatorPhase noiseJitterCMOSMaterials scienceFrequency offsetDelay line oscillatorElectrical engineeringDigitally controlled oscillatorVoltage-controlled oscillatorOptoelectronicsLocal oscillatorPhysicsEngineeringOpticsVoltageLaser

Abstract

fetched live from OpenAlex

This thesis proposes a novel, all synthesized, Injection Locked Ring Oscillator (ILRO).It employs a digitally tunable oscillator and a pulse injection locking technique.The frequency tuning range of the free running oscillator is from 210 MHz to 1.8 GHz with a 1.1 volt power supply.The tuning range from 1.0 to 1.8 GHz can be achieved with 215 tuning steps with a maximum step size of 11.2 MHz, that is well within the worst case 75 MHz (3rd sub-harmonic) and 32 MHz (9 th sub-harmonic) locking range of the oscillator.The design occupies 127.5 um by 31.5 um of chip area and is implemented in TSMC's 65nm CMOS technology.For 3rd harmonic injection locking, the ILRO's RMS jitter is 192.7 fs (1 KHz to 40 MHz) with a phase noise of -130.9 dBc/Hz at 1 MHz offset from the 1.62 GHz carrier while consuming 7.15 mW of power.4 Chapter: ILRO Simulation Results ..........

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 science0.0000.000
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 head0.011
GPT teacher head0.258
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 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
GenreMethods

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
Published2017
Admission routes1
Has abstractyes

Explore more

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