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Record W2759538091 · doi:10.1109/lmwc.2017.2750028

Wideband Hybrid Coupler With Electrically Switchable Phase-Difference Performance

2017· article· en· W2759538091 on OpenAlexaff
Kejia Ding, Ahmed A. Kishk

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsHybrid couplerWidebandPower dividers and directional couplersPhase differenceBandwidth (computing)Impedance matchingElectrical impedanceQuadrature (astronomy)Electronic engineeringElectric power transmissionTransmission linePhase (matter)Topology (electrical circuits)OpticsPhysicsComputer scienceElectrical engineeringEngineeringTelecommunications

Abstract

fetched live from OpenAlex

A wideband hybrid coupler with an adjustable output phase difference with equal power division is proposed. A compact, low-loss and low-cost reconfigurable transmission line with electrically switchable equivalent characteristic impedance and length is introduced and adopted in this design, which is based on a two-section quadrature hybrid structure. Additionally, only two bias points are needed in this hybrid coupler to operate six switches synchronously and provide three output phase differences; 90° and 90 ± a° (a ≤ 30° has been verified). Good matching, isolation, and equal power division are obtained under all phase-difference possibilities. Two examples of a = 15° and 30° are fabricated and measured for 2.4-GHz applications. Testing results demonstrate satisfying properties including the notably stable phase difference with an error less than ±6° over 30% frequency bandwidth. The presented hybrid couplers would be appropriate for Butler matrices to increase the number of possible beams, which will be more than the number of ports.

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 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 categoriesMeta-epidemiology (narrow)
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 score0.108
Threshold uncertainty score1.000

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 head0.013
GPT teacher head0.204
Teacher spread0.192 · 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 teacher head, not a consensus.

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

Citations32
Published2017
Admission routes1
Has abstractyes

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