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Record W4402802589 · doi:10.1109/lmwt.2024.3462729

Dual Band Dual Mode Substrate Integrated Waveguide Filter With Mixed Coupling

2024· article· en· W4402802589 on OpenAlexaff
Peng Chu, Mengjie Luo, Wenyu Zhang, Fang Zhu, Leilei Liu, Ke Wu

Bibliographic record

VenueIEEE Microwave and Wireless Technology Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
FundersNanjing University of Posts and TelecommunicationsNational Natural Science Foundation of China
KeywordsSubstrate couplingDual modeWaveguideCoupling (piping)Dual (grammatical number)Materials scienceSubstrate (aquarium)Multi-band deviceWaveguide filterOptoelectronicsFilter (signal processing)Mixed modeElectronic engineeringComputer scienceTelecommunicationsElectrical engineeringEngineeringPrototype filterComposite materialFilter designGeologyArt

Abstract

fetched live from OpenAlex

This letter presents a dual-band substrate integrated waveguide (SIW) filter based on the dual modes of TE101 and TE102 in multilayer structures. Its middle metal layers feature mixed-coupling structures, where the slots implement independent magnetic coupling for the TE101 and TE102 bands, and the holes implement additional electric coupling for the TE101 band. It can independently control the dual bands and their transmission zeros (TZs), allowing for flexible design and controllable selectivity. A prototype is provided with independent dual bands and controllable TZs located between them. The proposed technique should be effective for developing high-performance dual-band SIW filters in microwave and wireless circuits and systems.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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

Citations14
Published2024
Admission routes1
Has abstractyes

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