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Record W4293647056 · doi:10.36227/techrxiv.20692573.v1

Reconstruction of Arbitrarily Shaped Sources with Electromagnetic Time-Reversal and Kurtosis

2022· preprint· en· W4293647056 on OpenAlexaff
Jun Cai, Xiaoyao Feng, ZHIZHANG CHEN, Yuehe Ge, Zhimeng Xu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsDalhousie University
FundersNational Natural Science Foundation of China
KeywordsKurtosisErgodic theoryPoint (geometry)Computer scienceAlgorithmPhysicsAcousticsMathematicsMathematical analysisGeometryStatistics

Abstract

fetched live from OpenAlex

The time reversal method has been shown to be capable of reconstructing electromagnetic sources. However, in the past, most sources reconstructed are point sources that may not be often seen in practical situations. This paper presents preliminary studies on the time-reversal reconstruction of the sources with arbitrary geometrical shapes and with finite frequency bandwidths. Our results show that the time-reversal method, incorporating the Kurtosis, can effectively find the locations, excitation, and band-limited arbitrarily shaped sources. In addition, in an ergodic cavity, a single sensor is adequate to reconstruct the sources with reduced operational cost and complexity.This paper lays the groundwork for further development of the TR method for its uses in realistic scenarios of source reconstructions.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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