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Record W2738794741 · doi:10.1049/iet-spr.2017.0074

Transformed cubature quadrature Kalman filter

2017· article· en· W2738794741 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIET Signal Processing · 2017
Typearticle
Languageen
FieldComputer Science
TopicTarget Tracking and Data Fusion in Sensor Networks
Canadian institutionsMcGill University
Fundersnot available
KeywordsQuadrature (astronomy)Kalman filterAlgorithmFilter (signal processing)CovarianceMathematicsExtended Kalman filterTransformation (genetics)Computer scienceApplied mathematicsControl theory (sociology)StatisticsArtificial intelligenceComputer vision

Abstract

fetched live from OpenAlex

An orthogonal transformation is applied to the cubature quadrature (CQ) points which are used to approximate the intractable integrals appeared during the estimation of states of a non‐linear system. With the help of a theorem, it is shown that the transformed points reduce the higher order moments (HOM) appeared while approximating the mean and covariance. As the HOM act as residue, the proposed method results in an improved filtering accuracy. Further, the proposition is extended in delayed measurement environment. The proposed method has been implemented for two different simulation problems. The simulation results reveal that at the same computational load, the filter with transformed CQ points provides higher accuracy compared with the filter with ordinary CQ points. The performance has been verified in the delayed measurement environment and an improved accuracy has been reported.

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.

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 categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.271
Teacher spread0.249 · 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