MétaCan
Menu
Back to cohort
Record W3204697497 · doi:10.1002/cta.3142

Estimating phase error using a Hilbert transform‐based time‐domain technique

2021· article· en· W3204697497 on OpenAlex
Abdulwadood A. Al–Ali, Ahmed S. Elwakil, Brent Maundy, Anis Allagui, Mohamed B. Elamien

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Circuit Theory and Applications · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Electrical Measurement Techniques
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFrequency domainOffset (computer science)AlgorithmPhase noiseHilbert transformComputationHilbert spectral analysisFrequency offsetTime domainComputer scienceInstantaneous phaseNoise (video)Hilbert–Huang transformRoot mean squareNoise powerElectronic engineeringMathematicsSpectral densityPower (physics)TelecommunicationsMathematical analysisWhite noiseEngineeringPhysicsElectrical engineeringArtificial intelligenceOrthogonal frequency-division multiplexing

Abstract

fetched live from OpenAlex

Summary Measuring phase noise in oscillators is crucial in communication systems, vibration analysis, and frequency synthesizers. Traditionally, this measurement is done in frequency domain by estimating the ratio of the power density at an offset frequency from the carrier to the power of the carrier signal. This approach is hardware intensive and dependent on the the offset frequency, for which there exists no standard. Here, we propose an alternative method to quantify phase noise but in the time domain in the form of a root‐mean‐square true phase angle deviation. This is done using a self‐created reference signal and by applying the Hilbert transform to generate a complex analytic signal from the real time‐domain data sequence. This enables the computation of instantaneous metrics such as phase noise. Simulations and experimental results are provided to validate the proposed technique. In addition, its relationship to the origin of phase noise is mathematically explained.

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: Methods · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.428

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 head0.019
GPT teacher head0.308
Teacher spread0.290 · 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