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Record W2913793352 · doi:10.1109/tmtt.2019.2895532

Cascading Fundamental Building Blocks With Frequency-Dependent Couplings in Microwave Filters

2019· article· en· W2913793352 on OpenAlexaff
Ping Zhao, Ke Wu

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTopology (electrical circuits)Prototype filterElectronic engineeringNetwork synthesis filtersFilter (signal processing)DimensioningResonatorWaveguide filterComputer scienceFilter designCoupling (piping)Band-pass filterDistributed element filterEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Frequency-dependent coupling (FDC) emerges as a new method to introduce the finite-position transmission zeros (TZs) in the synthesis and design of filtering networks. In this paper, several fundamental building blocks with FDCs are introduced and studied. The higher order filters with many TZs can be constructed by cascading these fundamental building blocks. As compared with the conventional coupled-resonator filters with only constant couplings, the inclusion of FDCs can potentially create more TZs with the same coupling topology. It is also shown that to realize the same TZs, a filter can be realized in a simplified structure with less cross-couplings by using FDCs. In this paper, one complete filter design procedure is illustrated, including the steps of the circuit model synthesis by the method introduced in this paper, physical dimensioning of the filter by the electromagnetic simulation and measurement of the fabricated filter. The measurement results are in very good agreement with the theoretical predictions, which validates the modular design strategy for filters with FDCs.

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 score0.371
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 integrity0.0000.001
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 head0.204
Teacher spread0.198 · 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

Citations55
Published2019
Admission routes1
Has abstractyes

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