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Record W2039727791 · doi:10.1049/iet-cds:20060054

Manchester encoded bandpass sigma–delta modulation for RF class D amplifiers

2007· article· en· W2039727791 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 Circuits Devices & Systems · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsSimon Fraser UniversityWestern University
Fundersnot available
KeywordsDelta-sigma modulationAmplifierBand-pass filterPhoton upconversionCoding (social sciences)Electronic engineeringModulation (music)PhysicsTopology (electrical circuits)Computer scienceElectrical engineeringMathematicsEngineeringOptoelectronicsCMOSAcousticsDoping

Abstract

fetched live from OpenAlex

An analysis of a continuous-time bandpass sigma–delta modulator in a configuration with an upconverter is given for a RF class D amplifier application. The upconverter multiplies the modulator pulse train with a synchronised clock signal and maps each modulator bit to an integer multiple k of a (+1, −1) or (−1, +1) pattern depending on the sign of the modulator bit. The upconversion is equivalent to an extension of Manchester encoding, which is usually defined for k=1. The analysis focuses on evaluating the impact of upconversion on the modulator coding efficiency and the average pulse period. A design equation is derived, which shows that coding efficiency is dependent only on the upconversion frequency ratio, while the average pulse period depends only on k. The equations provide a designer with a way of evaluating the trade-offs in the amplifier system and show that encoding with k=1 is the most efficient configuration for maximising coding efficiency and minimising switching power loss.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.254
Teacher spread0.230 · 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