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Record W2161759144 · doi:10.1002/mop.26301

A novel Doherty power amplifier with self‐adaptive biasing network for efficiency improvement

2011· article· en· W2161759144 on OpenAlex
Shichang Chen, Quan Xue

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsBiasingAmplifierGate driverPower (physics)Electronic engineeringMicrowaveElectrical engineeringPower-added efficiencyVoltageEngineeringRF power amplifierPhysicsTelecommunicationsCMOS

Abstract

fetched live from OpenAlex

Abstract A Doherty power amplifier (DPA) with a self‐adaptive biasing circuit is presented in this letter. The proposed structure is integrated into the gate biasing network of the peaking power amplifier (PA), and then the gate voltage can be adaptively adjusted with the input power. Due to the presence of this simple but effective circuit, the peaking PA can approach the ideal power transfer characteristic which results in better efficiency than the conventional design with constant biasing. The proposed circuit is implemented and compared with both the conventional DPA and a single Class‐AB PA. 12% and 34% power added efficiency improvements are achieved at 6 dB backoff, respectively. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:2586‐2589, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26301

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: Methods · Consensus signal: none
Teacher disagreement score0.372
Threshold uncertainty score0.909

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 head0.014
GPT teacher head0.194
Teacher spread0.180 · 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