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Record W2124454658 · doi:10.1109/iscas.2005.1465628

An All-Digital Data Recovery Circuit Optimization using Matlab/Simulink

2005· article· en· W2124454658 on OpenAlexafffund
Saima Ahmed, T. Kwaśniewski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsCarleton University
FundersGovernment of Ontario
KeywordsJitterComputer scienceSoftware portabilityMATLABData recoveryInterval (graph theory)DetectorElectronic engineeringReal-time computingComputer hardwareEngineering

Abstract

fetched live from OpenAlex

The design of an all-digital data recovery (DR) circuit requires careful system-level design space exploration. The advantages of an all-digital implementation are the ease of portability and reduced time-to-market across fabrication processes and with reducing feature sizes. For a selected architecture, this paper explores the effects of sweeping the bit detection interval of a bang-bang phase detector, the phase update interval, and the number of clock phases used for data recovery using a Matlab/Simulink model. The simulation results show the variation of jitter tolerance of the DR circuit with respect to the above parameters. An all-digital architecture can be made adaptive to jitter conditions, if the design trade-offs are known a priori. A statistical graphing/analysis tool is used to present the 3D logarithmic scatter plots.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.724
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

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 communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.074
GPT teacher head0.296
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations8
Published2005
Admission routes2
Has abstractyes

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