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Record W1719451509 · doi:10.1109/iscas.2006.1693367

A CMOS circuit for embedded GHz measurement of digital signal rise time degradation

2006· article· en· W1719451509 on OpenAlexafffund
Mona Safi-Harb, Gordon W. Roberts

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsMcGill University
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsJitterUndersamplingElectronic engineeringComputer scienceCMOSTime domainAsynchronous communicationSampling (signal processing)Static timing analysisAsynchronous circuitDetectorChipSIGNAL (programming language)Clock signalSynchronous circuitEngineeringTelecommunications

Abstract

fetched live from OpenAlex

An embedded diagnosis circuit for quantifying the degradation in digital signals rise/fall time is presented. The proposed measurement technique differs from previous approaches in many ways. Firstly, it avoids the use of undersampling which can become problematic at high speeds; instead, it relies on a real-time asynchronous sampling approach which eliminates the distortion jeopardy imposed by the front-end sampling network, sampling clock jitter, and delay line jitter for GHz range applications. Secondly, the information is processed in the time domain which makes use of the recent developments in time-domain amplification (Oulmane and Roberts, 2004). Thirdly, a dynamic current generation technique is used to achieve great reduction in static power dissipation and allows the front-end level-crossing detector to work at such high speeds. The circuit was implemented in a standard 0.18-mum CMOS process. Simulation results show the feasibility of the proposed approach. Preliminary experimental results are also presented. The proposed circuit can be equally used to perform on-chip analog slew rate measurement

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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.021
GPT teacher head0.211
Teacher spread0.190 · 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

Citations3
Published2006
Admission routes2
Has abstractyes

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