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Record W3216440937 · doi:10.1109/mwsym.2002.1011772

Application of C-COM for microwave integrated-circuit modeling

2003· article· en· W3216440937 on OpenAlexaff
K. Lan, S.K. Chaudhuri, S. Safavi‐Naeini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFinite-difference time-domain methodMicrostripBoundary value problemdBcMicrowaveTransmission lineElectronic engineeringTransformerElectrical impedanceComputer scienceElectronic circuitOperator (biology)Topology (electrical circuits)AcousticsMathematical analysisPhysicsMathematicsElectrical engineeringEngineeringTelecommunicationsOpticsVoltageCMOS

Abstract

fetched live from OpenAlex

The concurrent complementary operators method (C-COM) is extended for the FDTD simulation of microwave integrated circuits for the first time. Fields in the boundary layers are computed twice with the dispersive boundary condition (DBC) and its complementary operator to truncate the FDTD lattices. The two simulations are averaged to annihilate the first order reflections from the truncated boundary. Numerical error analysis show that the reflections are further suppressed by at least 20 dB due to the implementation of complementary operators, and the setup of parameters becomes easier and more robust. A flexible and highly efficient absorbing boundary condition for guided wave problems is thus obtained through the combination of C-COM and DBC. Simulation results for a modified microstrip transmission line and a microstrip impedance transformer are given to validate this method.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.265
Teacher spread0.242 · 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
Published2003
Admission routes1
Has abstractyes

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