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Record W2158959564 · doi:10.1109/tvlsi.2003.810787

A digitally programmable delay element: design and analysis

2003· article· en· W2158959564 on OpenAlexaff
Mohammad Maymandi‐Nejad, Manoj Sachdev

Bibliographic record

VenueIEEE Transactions on Very Large Scale Integration (VLSI) Systems · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDelay calculationGroup delay and phase delayElmore delayDelay-locked loopComputer scienceElectronic engineeringPropagation delayDigital delay lineElectronic circuitStatic timing analysisDelay line oscillatorControl theory (sociology)EngineeringElectrical engineeringDigital signal processingDigital signalTelecommunicationsPhase-locked loopControl (management)

Abstract

fetched live from OpenAlex

Variable delay elements are often used to manipulate the rising or falling edges of the clock or any other signal in integrated circuits (ICs). Delay elements are also used in delay locked loops (DLLs). Although, a few types of digitally controlled delay elements have been proposed, an analytical expression for the delay of these circuits has not been reported. In this paper, we propose a new delay element architecture and develop an analytical equation for the output voltage and an empirical relation for the delay of the circuit. The proposed circuit exhibits improved delay characteristics over previously reported digitally controlled delay elements.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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

Citations168
Published2003
Admission routes1
Has abstractyes

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