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Record W2758026207 · doi:10.1109/mwscas.2017.8053014

Low-power all-digital ΔΣ TDC with bi-directional gated delay line time integrator

2017· article· en· W2758026207 on OpenAlexaff
Young Jun Park, Fei Yuan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsIntegratorOversamplingIntegrating ADCCMOSElectronic engineeringCapacitorJitterTime delay and integrationElectrical engineeringSIGNAL (programming language)Noise (video)Computer sciencePhysicsVoltageEngineeringOptics

Abstract

fetched live from OpenAlex

This paper presents a low-power time integrator and its applications in an all-digital first-order ΔΣ time-to-digital converter (TDC). The time integrator is realized using a bi-directional gated delay line (BD-GDL) with time variable to be integrated as the gating signal. The integration of the time variable is obtained via the accumulation of the charge of the load capacitor and the logic state of gated delay stages. Issues affecting the performance of the time integrator and TDC are examined. An all-digital first-order ΔΣ TDC utilizing the time integrator was designed in an IBM 130 nm 1.2 V CMOS technology. A sinusoid time input of 430 ps amplitude and 231 kHz frequency with oversampling ratio 54 was digitized by the modulator. The TDC provides first-order noise-shaping and a SNR of 39.98 dB over the signal band 36 ~ 231 kHz consuming 46 μW.

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: none
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.229
Teacher spread0.220 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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