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Record W2127345503 · doi:10.1109/tmtt.2009.2017362

A New Approach to Canonical Dual-Mode Cavity Filter Design

2009· article· en· W2127345503 on OpenAlexaff
M. Bekheit, S. Amari, Fabien Seyfert

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
KeywordsPassbandCanonical formTopology (electrical circuits)Filter (signal processing)Coupling (piping)Dual modeRepresentation (politics)Dual (grammatical number)Prototype filterMathematicsBasis (linear algebra)Matrix representationMatrix (chemical analysis)Filter designControl theory (sociology)Mode couplingPhysicsMathematical analysisBand-pass filterElectronic engineeringOpticsComputer scienceEngineeringGeometryPure mathematicsMaterials scienceQuantum mechanicsElectrical engineeringCombinatorics

Abstract

fetched live from OpenAlex

This paper presents a new approach to the design of canonical dual-mode cavity filters within representation theory. Instead of the folded canonical coupling matrix, which results from using the resonances of the empty cavities as a basis, a representation based on the resonances of the cavities with all perturbations present is used. The resulting coupling matrix takes the form of a cul-de-sac configuration. For canonical dual-mode filters with a symmetric response, it allows direct design of the entire structure, except of the input cavity that requires optimization. A sixth-order filter with two symmetrically located transmission zeros is presented to document the validity of the approach. A sixth-order filter with two transmission zeros above the passband is also presented.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
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)0.0030.001

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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