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Record W2921156937 · doi:10.1049/el.2019.0562

Design of a narrow dual‐band BPF with an independently‐tunable passband

2019· article· en· W2921156937 on OpenAlexaff
Seyed Mohammad Hadi Mousavi, Seyed Vahab Al‐Din Makki, Sh. Alirezaee, Seyed-Ali Malakooti

Bibliographic record

VenueElectronics Letters · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPassbandBand-pass filterStopbandResonatorElliptic filterTransition bandPhysicsFilter (signal processing)Electronic engineeringPrototype filterAcousticsComputer scienceOpticsBandwidth (computing)TelecommunicationsLow-pass filterEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Using polygonal resonators and bended lines, a new type of dual‐band bandpass filter (BPF) is presented generating a fixed passband centred at 2.70 ( f 01 ) and an independently‐electronically tunable passband ( f 02 ) which can be tuned between 3.65 and 6.51 GHz (56% tuning range). The measured results indicate that the return losses of both passbands are >21 dB throughout the tuning range. Furthermore, the use of bended lines leads to extremely small size of , where is the guided wavelength at the lowest working frequency ( f 01 ). The proposed BPF also benefits from an ultra‐wide upper stopband from 7.03 up to 14.41 GHz (based on 21 dB points), suppressing unwanted signal by more than 21 dB considered as a positive point. The filter prototype is investigated in four design stages with the LC analysis to support the design process theoretically and fabrication results to validate the design practically.

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 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 score0.321
Threshold uncertainty score0.759

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 head0.005
GPT teacher head0.171
Teacher spread0.166 · 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.

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

Citations7
Published2019
Admission routes1
Has abstractyes

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