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Record W2116531235 · doi:10.1109/iscas.2008.4542105

A Passive Filter Aided Timing Recovery Scheme

2008· article· en· W2116531235 on OpenAlexaff
F. A. S. Musa, Anthony Chan Carusone

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsClock recoveryCMOSData recoveryFilter (signal processing)High-pass filterElectronic engineeringComputer scienceScheme (mathematics)Low-pass filterProcess (computing)EngineeringElectrical engineeringMathematicsComputer hardwareClock signalJitter

Abstract

fetched live from OpenAlex

This paper presents a passive Alter for the front end of a high speed serial link receiver to aid timing recovery. The Alter provides simultaneous lowpass and highpass transfer characteristics to generate the data and its slope respectively. Slope detection is demonstrated at 10-Gb/s. As a proof of concept, the Alter was used to extract a 2-GHz clock from a 2-Gb/s 231- 1 random data sequence based on a modified minimum mean squared error (MMSE) criterion. The circuit is fabricated in a 0.18 mum CMOS process and consumes 21.6 mW from a 1.8 V supply.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.031
GPT teacher head0.226
Teacher spread0.196 · 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 designSimulation or modeling
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

Citations1
Published2008
Admission routes1
Has abstractyes

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