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Record W2166504427 · doi:10.1109/aps.2010.5561234

Wavelet electromagnetic field processing: Multidimensional fast wavelet transform decomposition of time and frequency domain electromagnetic fields

2010· article· en· W2166504427 on OpenAlexaff
Adrian Ngoly, S. McFee

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsWavelet transformWaveletElectromagnetic fieldSecond-generation wavelet transformHarmonic wavelet transformComputational electromagneticsElectromagnetic radiationElectromagneticsStationary wavelet transformDiscrete wavelet transformFrequency domainTime domainFast wavelet transformPhysicsComputer scienceMathematical analysisMathematicsOpticsArtificial intelligenceComputer vision

Abstract

fetched live from OpenAlex

This paper presents a wavelet processing method for time and frequency domain electromagnetic fields for the rigorous and efficient inspection of the wave physics properties of transient and time-harmonic electromagnetic field solutions. More specifically, this research expounds upon the construction of (discrete) isotropic Fast Wavelet Transform (FWT) decompositions for multidimensional time and frequency domain electromagnetic fields with applications to electromagnetic radiation and scattering. In this work, discretely sampled space-time and space-frequency electromagnetic fields are processed using the (isotropic) Fast Wavelet Transform (FWT) algorithm [5], customized here to address real (IR) and complex (C) valued electromagnetic vector fields. Moreover, the structure and physical interpretation of the wavelet coefficients are described in detail.

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 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 score0.259
Threshold uncertainty score0.566

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 head0.003
GPT teacher head0.223
Teacher spread0.220 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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