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Record W2032711348 · doi:10.1155/2010/415315

<i>X</i>‐Parameter Measurement of Pulse‐Compression Nonlinear Transmission Lines

2009· article· en· W2032711348 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Electrical and Computer Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsCarleton University
Fundersnot available
KeywordsNonlinear systemWaveformPulse compressionTime domainElectronic engineeringFrequency domainSIGNAL (programming language)Network analyzer (electrical)Transmission (telecommunications)MicrowaveCompression (physics)Computer sciencePulse (music)AcousticsMaterials scienceEngineeringPhysicsElectrical engineeringTelecommunicationsVoltage

Abstract

fetched live from OpenAlex

X ‐parameters provide a powerful and eminently practical solution for interoperable measurement, modeling, and simulation of nonlinear microwave and RF components. Using X ‐parameters to do large‐signal measurements has been brought into the spotlight. This paper introduces a new X ‐parameter application: measuring large‐signal behaviour of pulse‐compression nonlinear transmission lines (NLTLs). A specially configured Nonlinear Vector Network Analyzer (NVNA) was used to measure the X ‐parameters in the frequency‐domain, and then the measured data was transformed into a nonlinear time‐domain waveform. The results show both rise‐time and fall‐time reduction (double‐edge compression) as expected and indicate that this newly developed X ‐parameter method implemented with an NVNA could correctly predict NLTLs′ pulse‐compression performance.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score0.531

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 head0.194
Teacher spread0.183 · 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