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Record W2164744386 · doi:10.1109/tftsa.1992.274183

An interpretation of the spectrogram for discrete-time signals

2003· article· en· W2164744386 on OpenAlexaff
Mathews Jacob, Paul Fortier

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMachine Fault Diagnosis Techniques
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSpectrogramConvolution (computer science)Interpretation (philosophy)Time–frequency analysisWigner distribution functionDiscrete-time signalDiscrete time and continuous timeDiscrete Fourier transform (general)AlgorithmTime domainFrequency domainDiscrete frequency domainComputer scienceMathematicsSpeech recognitionFourier transformArtificial intelligenceMathematical analysisFourier analysisPhysicsDigital signal processingShort-time Fourier transformStatisticsComputer visionAnalog signal

Abstract

fetched live from OpenAlex

The spectrogram for continous-time signals can be expressed as a convolution of two Wigner distributions in the time-frequency plane. Definitions exist for the discrete-time spectrogram and the discrete-time Wigner distribution, each with its own periodicity in the frequency domain. The authors demonstrate how the discrete-time spectrogram is related to a convolution of discrete-time Wigner distributions in spite of this noticeable incompatibility concerning periodicity. The result can be considered as the counterpart of the relation existing for continuous-time signals.>

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)0.004
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.004
GPT teacher head0.276
Teacher spread0.271 · 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
Published2003
Admission routes1
Has abstractyes

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