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Record W2542203766 · doi:10.1109/ias.2001.955929

Converter nonintegral harmonics from AC network resonating with DC network

2002· article· en· W2542203766 on OpenAlexaff
Lianxiang Tang, Boon‐Teck Ooi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsMcGill University
Fundersnot available
KeywordsHarmonicsCorrectnessTotal harmonic distortionControl theory (sociology)Noise (video)Harmonic analysisModulation (music)Electronic engineeringComputer scienceDC biasPhysicsEngineeringAlgorithmElectrical engineeringAcousticsVoltageArtificial intelligence

Abstract

fetched live from OpenAlex

Integral harmonics come from the switching pattern of the modulation method. Nonintegral harmonics, on the other hand, are initiated by random noise that becomes amplified and sustained by the AC network resonating with the DC network. A comprehensive theory of their origins is presented. Its correctness is justified by digital simulations. It is then shown that an efficient method of predicting their potential occurrences is by eigenvalue analysis. The objective of THD compliance can be met by: (i) avoidance by design of network parameters; and (ii) suppression by active filtering. Some directions of parameter design are given. A simulation result is presented showing that an active filtering method is promising.

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.920
Threshold uncertainty score0.998

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)0.0030.000

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 head0.173
Teacher spread0.156 · 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 teacher head, not a consensus.

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

Citations7
Published2002
Admission routes1
Has abstractyes

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