MétaCan
Menu
Back to cohort
Record W2164040051 · doi:10.1109/mwscas.2007.4488754

Precise free-running period synthesizer (FRPS) with process and temperature compensation

2007· article· en· W2164040051 on OpenAlexaff
Bill Pontikakis, Francois-R. Boyer, Yvon Savaria, Hung Tien Bui

Bibliographic record

VenueConference proceedings · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversité du Québec à ChicoutimiPolytechnique Montréal
Fundersnot available
KeywordsJitterField-programmable gate arrayComputer scienceClock generatorVHDLCompensation (psychology)Computer hardwareProcess (computing)Frequency synthesizerCMOSEmbedded systemElectronic engineeringPhase-locked loopEngineeringClock signalOperating systemTelecommunications

Abstract

fetched live from OpenAlex

This paper proposes an all-digital, automated, clock generator based on a free-running oscillator that can generate arbitrarily precise frequencies. The entire system can be implemented using standard cells and even has a compensation system to mitigate the effects of environmental variations on frequency. The design is implemented in VHDL and synthesized using Artisan standard-cells in TSMC’s 180nm CMOS technology. Post-layout timing analysis shows that the proposed free-running period synthesizer (FPRS) can operate at a frequency of up to 175 MHz. The architecture was also validated with an implementation on a Xilinx’s Spartan 3 FPGA that works at 80 MHz. In both implementations, the worst case peak to peak jitter of the output clock is equal to one period of the free-running oscillator.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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

Citations9
Published2007
Admission routes1
Has abstractyes

Explore more

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