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Record W2003581116 · doi:10.1109/temc.2012.2213590

Digital Active EMI Control Technique for Switch Mode Power Converters

2012· article· en· W2003581116 on OpenAlexaff
Djilali Hamza, Mei Qiu

Bibliographic record

VenueIEEE Transactions on Electromagnetic Compatibility · 2012
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsQueen's University
Fundersnot available
KeywordsEMIElectromagnetic interferenceElectronic engineeringConvertersNoise (video)Conducted electromagnetic interferenceEngineeringLine filterCommon-mode signalElectrical engineeringAttenuationFilter (signal processing)Computer scienceDigital signal processingPhysicsVoltageAnalog signal

Abstract

fetched live from OpenAlex

A novel electromagnetic interference (EMI) suppression technique based on field programmable logic array technology is proposed to provide a significant EMI noise attenuation for switch-mode power converters. This technique uses noise acquisition at very high-sampling rate. The noise signal is processed to invert its phase angle and reconstructed with high fidelity to counteract the noise signal before reaching the line impedance stabilization network. Thus, high noise attenuation is achieved. The new technique is validated through simulation and experimental results of a single-phase ac–dc converter. The proposed technique can be extended to dc/dc converters to replace the conventional passive EMI filter where the PCB space is restricted. This technique can be a desired contingent in industrial applications where space is a major design constraint.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.225
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations34
Published2012
Admission routes1
Has abstractyes

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