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Record W1481438536 · doi:10.1109/epep.2004.1407584

Modeling of transmission lines with textured ground planes and investigation of data transmission by generating eye diagrams

2005· article· en· W1481438536 on OpenAlexaff
J.C.W. Ho, Quanyan Zhu, Ramesh Abhari

Bibliographic record

VenueElectrical Performance of Electronic Packaging · 2005
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsMcGill University
Fundersnot available
KeywordsTransmission lineScattering parametersElectric power transmissionEquivalent circuitTransmission (telecommunications)Ground planeCoupling (piping)Transverse planeElectronic engineeringLine (geometry)Network modelDistributed element modelComputer scienceTopology (electrical circuits)OpticsAcousticsGeometryPhysicsMaterials scienceEngineeringTelecommunicationsElectrical engineeringStructural engineeringMathematicsVoltage

Abstract

fetched live from OpenAlex

In this work, data transmission in transmission lines containing textured ground planes in the power distribution network is investigated. A lumped element model is developed to generate eye diagrams and circuit simulations are compared with measurements. A circuit model for a transmission line with an EBG ground plane is introduced. The circuit model for the EBG structure is developed based on using LC components and considering each patch as a parallel-plate transmission line. This modeling strategy allows including two important features to the individual LC stages representing the EBG surface: coupling to the signal line, and transverse loading of adjacent patches in the EBG structure. The circuit model parameters are calculated by using closed-form relations and applying the physical dimensions of the structure-under-test. The proposed model is employed to generate the scattering-parameter graphs and eye diagrams, which are compared with full-wave simulations and measurements to ensure validation of the results in both frequency and time domains.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.737

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)0.0000.000

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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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 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

Citations7
Published2005
Admission routes1
Has abstractyes

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