MétaCan
Menu
Back to cohort
Record W2162092442 · doi:10.1109/tmtt.2009.2027165

A Direct Design Technique for Dual-Mode Inline Microwave Bandpass Filters

2009· article· en· W2162092442 on OpenAlexaff
M. Bekheit, S. Amari

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2009
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsBand-pass filterMicrowaveWaveguide filterElectronic engineeringWaveguideCoupling (piping)Discontinuity (linguistics)Modular designScattering parametersTopology (electrical circuits)EngineeringPhysicsPrototype filterFilter (signal processing)Computer scienceFilter designOpticsMathematicsElectrical engineeringTelecommunicationsMathematical analysisMechanical engineering

Abstract

fetched live from OpenAlex

This paper presents a modular, direct, and accurate design technique for microwave dual-mode bandpass filters. The design is based on the generalized scattering matrix of each discontinuity in the structure. Different propagating modes in the same waveguide section are used in the representation of such matrices in order to facilitate the design. Different representations of the coupling matrix are also used. These are chosen to take into account the boundary conditions inside the cavity and the dominant physics of the problem at each stage. The loading of the resonances by the coupling elements is accurately calculated at each design step by exploiting a circuit based on propagation instead of resonance. Design examples of filters of fourth and eighth orders in rectangular and circular cavities are presented. Excellent initial designs are achieved with little or no need for any optimization.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations21
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Microwave Theory and TechniquesSame topicMicrowave Engineering and WaveguidesFrench-language works237,207