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Record W2134988923 · doi:10.1109/isie.2006.295739

Development and Experimental Testing of a Single-Phase B-Spline-Based SPWM Inverter

2006· article· en· W2134988923 on OpenAlexaff
S. A. Saleh, Md. Azizur Rahman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital Filter Design and Implementation
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsInverterDSPACEInsulated-gate bipolar transistorSpline (mechanical)Pulse-width modulationElectronic engineeringDigital signal processingDigital signal processorComputer scienceHarmonicControl theory (sociology)AlgorithmMathematicsVoltageEngineeringPhysicsElectrical engineeringAcousticsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents real-time implementation and testing of a new family of cardinal beta-spline carrier signals. These carrier signals are tested for a single phase (1Phi) sinusoidal pulse-width modulated (SPWM) voltage-source (VS) inverter. The conventional SPWM technique uses triangular carrier signals, which can be interpreted as a periodic form of the second order cardinal beta-spline function. The proposed family of carrier signals are periodic cardinal beta-spline functions of order higher than 2. An algorithm to implement different orders of periodic cardinal beta-spline functions is developed and implemented for experimental testing on a 1Phi VS 4-pulse IGBT SPWM inverter. The developed algorithm and the generation of SPWM switching pulses are executed by a dSPACE ds1102 digital signal processor (DSP) board. Test results demonstrate a significant performance improvement using proposed carrier signals, where output harmonic contents are reduced and the magnitude of the fundamental component is improved

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)0.001
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.075
GPT teacher head0.289
Teacher spread0.215 · 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

Citations13
Published2006
Admission routes1
Has abstractyes

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