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Record W2760821253 · doi:10.1109/mwsym.2017.8058776

Time domain poly-harmonic distortion models of RF transistors and its extraction using a hybrid passive/active measurement setup

2017· article· en· W2760821253 on OpenAlex
Amir-Reza Amini, Slim Boumaiza

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Waterloo
FundersKeysight Technologies
KeywordsTransistorTotal harmonic distortionAmplifierNonlinear systemElectronic engineeringNonlinear distortionFrequency domainRadio frequencyRF power amplifierIntermodulationTime domainTransistor modelScattering parametersComputer sciencePhysicsControl theory (sociology)Electrical engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

This paper presents a novel behavioral model of RF transistors under periodic stimulus that is mathematically equivalent to frequency domain Poly-Harmonic Distortion (PHD) models but is defined instead in the time domain. Given a fixed fundamental frequency for a periodic stimulus, a time domain PHD (TD-PHD) model that describes this periodic behavior consists of two nonlinear functions, each describing the large-signal response at one of the two ports of the RF transistor. In this model, the response at each port at any given time is a nonlinear time-invariant function of the stimulus at both ports throughout its entire RF period. Using a two-port hybrid passive/active multi-harmonic load-pull measurement setup, a 10W GaN packaged transistor biased in class AB is measured with a Nonlinear Vector Network Analyzer (NVNA). The predictive performance of the extracted model is validated against a power amplifier design that uses this RF transistor.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.754

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 communication0.0000.001
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 head0.044
GPT teacher head0.255
Teacher spread0.210 · 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

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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