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Record W2140745231 · doi:10.1109/iscas.1999.780628

Continuous-time adaptive-analog coaxial cable equalizer in 0.5 μm CMOS

2003· article· en· W2140745231 on OpenAlexaff
G.P. Hartman, Kenneth W. Martin, Angus McLaren

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in PLL and VCO Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCMOSIntersymbol interferenceCoaxial cableElectronic engineeringAdaptive equalizerElectrical engineeringFilter (signal processing)CoaxialChipComputer scienceDissipationEngineeringEqualizerPhysics

Abstract

fetched live from OpenAlex

The transmission of high-speed data on copper suffers from frequency-dependent losses that can cause significant intersymbol interference. The losses mainly arise from the increase in series resistance at high frequencies due to the skin effect. There are also dielectric losses, which are significant in the GHz range and higher. To correct for frequency dependent losses, an integrated circuit continuous-time analog filter is used. An on-chip adaptive control loop provides correction for any cable length. As part of the present research, many of the building blocks required for a CMOS implementation of the equalizer system have been designed and submitted for fabrication in a 0.5 /spl mu/m standard-digital-CMOS process. The equalizer is realized in an area of 1.1 mm/sup 2/, with power dissipation of 30 mW, using a 3.3 V power 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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.840
Threshold uncertainty score0.999

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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.

Study designNot applicable
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

Citations15
Published2003
Admission routes1
Has abstractyes

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