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Record W2044925215 · doi:10.1109/icassp.2007.367049

S-Transform with Frequency Dependent Kaiser Window

2007· article· en· W2044925215 on OpenAlex
Ervin Sejdić, Igor Djurović, Jin Jiang

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsWestern University
Fundersnot available
KeywordsFrequency domainEnergy (signal processing)Time–frequency analysisS transformWindow (computing)Window functionComputer scienceShort-time Fourier transformSIGNAL (programming language)AlgorithmMathematicsStatisticsFourier transformTelecommunicationsArtificial intelligenceWavelet transformSpectral densityComputer visionMathematical analysis

Abstract

fetched live from OpenAlex

A time-frequency signal analysis tool, known as S-transform, can suffer from poor energy concentration in the time-frequency domain. In this paper, a frequency dependent Kaiser window is presented for improving the energy concentration of the S-transform. The new window is analyzed using a set of test signals. The results indicate that the proposed scheme can significantly improve the energy concentration in the time-frequency domain in comparison with the standard S-transform.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.771
Threshold uncertainty score0.361

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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

Quick stats

Citations14
Published2007
Admission routes1
Has abstractyes

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