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Record W2128746719 · doi:10.1109/icics.2003.1292616

Cramer-Rao bounds for estimation of pure-tone signals' Azimuth-elevation arrival angles & polarization parameters & frequencies using a dipole-triad or a loop-triad

2004· article· en· W2128746719 on OpenAlexaff
C.K. Au Yeung, Kainam Thomas Wong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDirection-of-Arrival Estimation Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAzimuthDipoleCramér–Rao boundAmplitudePolarization (electrochemistry)Direction of arrivalTriad (sociology)PhysicsMultiple signal classificationComputational physicsAntenna (radio)AcousticsEstimation theoryOpticsAlgorithmComputer scienceTelecommunicationsChemistry

Abstract

fetched live from OpenAlex

This work derives new nonasymptotic and asymptotic Cramer-Rao lower bounds (CRB) for the estimation of multiple pure-tone incident signals' amplitudes, azimuth-elevation arrival-angles, polarization parameters, and frequencies, based on data observed from one dipole triad (composed of three spatially collocated but orthogonally oriented electrically short dipoles) or one loop-triad (composed of three spatially collocated but orthogonally oriented magnetically small loops). The incident sources are pure-tones at distinct frequencies, in contrast to the existing electromagnetic antenna-array signal-estimation CRB literature's modeling of all sources to be at the same carrier-frequency.

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)0.009
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.065
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.061
GPT teacher head0.340
Teacher spread0.279 · 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 designTheoretical or conceptual
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

Citations2
Published2004
Admission routes1
Has abstractyes

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