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Record W2171904356 · doi:10.1109/lpt.2010.2059004

Instantaneous Microwave Frequency Measurement Using a Photonic Microwave Filter Pair

2010· article· en· W2171904356 on OpenAlexaff
Shilong Pan, Jianping Yao

Bibliographic record

VenueIEEE Photonics Technology Letters · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMicrowaveFilter (signal processing)PhotonicsMicrowave engineeringMicrowave transmissionIntermediate frequencyOptical filterTransfer functionOpticsBand-pass filterElectronic engineeringRadio frequencyPhysicsAcousticsMaterials scienceComputer scienceTelecommunicationsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Photonics-assisted instantaneous microwave frequency measurement (IFM) has been a topic of interest recently. To perform IFM, an amplitude comparison function (ACF) that relates the microwave frequency to the microwave powers by which the microwave frequency can be estimated by measuring the microwave powers should be established. In this letter, a two-tap photonic microwave filter pair with complementary frequency responses is employed for achieving IFM. Thanks to the complementary nature of the transfer functions of the filter pair, a quasi-linear monotonically decreasing ACF over a large frequency band is obtained, which ensures an improved measurement range and accuracy. An experiment is performed. A microwave frequency measurement range as large as 36 GHz with a measurement accuracy better than ±0.2 GHz is experimentally demonstrated.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.226
Teacher spread0.206 · 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 designBench or experimental
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

Citations78
Published2010
Admission routes1
Has abstractyes

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