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Record W1935833027 · doi:10.1109/imtc.1997.604036

Active load characterization of a microwave transistor for oscillator design

2002· article· en· W1935833027 on OpenAlexaff
Pierre Berini, Fadhel M. Ghannouchi, R.G. Bosisio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave and Dielectric Measurement Techniques
Canadian institutionsPolytechnique MontréalUniversity of Ottawa
Fundersnot available
KeywordsTransistorMicrowaveElectrical impedanceElectronic engineeringActive loadSIGNAL (programming language)Electrical engineeringPower (physics)Monolithic microwave integrated circuitPort (circuit theory)Computer scienceEngineeringVoltagePhysicsTelecommunicationsCMOS

Abstract

fetched live from OpenAlex

This paper describes the use of a six-port active load measurement system to determine the optimal large-signal loading of transistors for the design of microwave oscillators providing maximum output power. Our system has been used to measure the optimal large-signal terminating impedance for a potentially unstable microwave transistor and to apply the device line characterization technique. This technique, which is used to characterize a negative resistance monoport and predict the level of oscillator output power, is implemented for the first time using active loading. An oscillator designed using our measurements generated an output power of 11.3 dBm at a frequency of 3.5 GHz. This result is in good agreement with the value predicted from the device line technique and our measurement system.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.038
GPT teacher head0.199
Teacher spread0.161 · 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
Published2002
Admission routes1
Has abstractyes

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