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Record W1496086628 · doi:10.1049/iet-map.2010.0037

Analytical approach to optimise the efficiency of switching mode power amplifiers loaded with distributed matching networks

2011· article· en· W1496086628 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

VenueIET Microwaves Antennas & Propagation · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAmplifierHarmonicElectronic engineeringPower (physics)Matching (statistics)High-electron-mobility transistorTransistorTransistor arrayEngineeringComputer scienceTopology (electrical circuits)Electrical engineeringMathematicsVoltageAcousticsPhysics

Abstract

fetched live from OpenAlex

This study describes the design methodology of optimising the power-added efficiency (PAE) of switching mode power amplifiers (SMPAs). To maximise efficiency, design optimisation of the harmonic loading networks using an analytical analysis approach is proposed. Indeed, by carefully designing a distributed harmonic control network at the output of the SMPA, the insertion loss through the load network can be minimised. To validate the PAE optimisation approach, two 10 W inverse class F power amplifiers (PAs) were designed, manufactured and tested at a frequency of 2.45 GHz using a GaN HEMT transistor. The first PA prototype was matched with a standard distributed harmonic loading network and the second with the proposed distributed harmonic loading network. The measured PAE and gain for the second prototype were improved by 3% and 0.17 dB to reach 73% and 14 dB, respectively.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.796
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.219
Teacher spread0.203 · 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