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Record W1911388298 · doi:10.1109/iscas.1999.780627

Differential 0.35 μm CMOS circuits for 622 MHz/933 MHz monolithic clock and data recovery applications

2003· article· en· W1911388298 on OpenAlexafffund
H. Djahanshahi, C.A.T. Salama

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of Toronto
FundersCMC Microsystems
KeywordsCMOSVoltage-controlled oscillatorPhase-locked loopElectronic engineeringComputer scienceFilter (signal processing)Integrated circuitChipData recoveryElectronic circuitCharge pumpIntegrated circuit designClock recoveryController (irrigation)Electrical engineeringVoltageEngineeringClock signalComputer hardwarePhase noiseCapacitorTelecommunications

Abstract

fetched live from OpenAlex

Fully-differential CMOS circuits are presented for high speed Clock and Data Recovery (CDR) applications. The design is part of an integrated physical layer controller for an OC-12 ATM system, but can be used in other systems operating in 622 MHz-933 MHz range. Building blocks are presented including novel designs for VCO and charge pump. Two chips are implemented in 0.35 /spl mu/m CMOS. One contains partitioned building blocks of a PLL-based CDR that, together with an external loop filter, can be used for flexible testing and application at a desired frequency. The other chip is a monolithic CDR with integrated loop filter particularly designed for application on 622 Mb/s NRZ data.

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)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.039
GPT teacher head0.278
Teacher spread0.238 · 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
Published2003
Admission routes2
Has abstractyes

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