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Record W2008791416 · doi:10.1109/icmew.2013.6618247

3D sound field reproduction using diverse loudspeaker patterns

2013· article· en· W2008791416 on OpenAlexaff
Hanieh Khalilian, Ivan V. Bajić, Rodney G. Vaughan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsLoudspeakerAcousticsSingular value decompositionComputer scienceSound recording and reproductionDirectional soundField (mathematics)Transfer functionHigh fidelityPhysicsMathematicsEngineeringAlgorithmElectrical engineering

Abstract

fetched live from OpenAlex

Sound field reproduction (SFR) in a cubic region is addressed using a finite planar array of loudspeakers with diverse radiation patterns. An acoustic transfer function (ATF) matrix that best approximates the desired field under a power constraint is found from singular value decomposition (SVD). The loudspeaker patterns are then derived to match the ATF. Free-space-based simulations indicate that in 3D SFR, higher order loudspeakers offer better reproduction fidelity than low-order patterns, as can be expected from the extra degrees of freedom, and as previously reported for 2D SFR. The optimized patterns turn out to be highly diverse, even if they are all of the same order. These would have to be implemented from sub-arrays or reconfigurable loudspeaker designs.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.995

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)0.0060.001

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 head0.035
GPT teacher head0.259
Teacher spread0.224 · 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
Published2013
Admission routes1
Has abstractyes

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