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Record W2011103363 · doi:10.1109/eumc.2005.1608917

Reconfigurable bandpass filter structure using an SPDT MEMS switch

2005· article· en· W2011103363 on OpenAlexaff
Carlos E. Saavedra

Bibliographic record

Venue2005 European Microwave Conference · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsQueen's University
Fundersnot available
KeywordsBand-pass filterFilter (signal processing)Microelectromechanical systemsVoltageElectronic engineeringTransient (computer programming)Electrical engineeringPhysicsTopology (electrical circuits)Computer scienceOptoelectronicsEngineering

Abstract

fetched live from OpenAlex

A concept for a bandpass reconfigurable filter structure capable of operating a two different passbands is presented. The circuit consists of two edge-coupled-line bandpass filters and a single-pole double throw MEMS switch. The incident signal enters a three-conductor set of coupled lines which feeds the two bandpass filters. The switch selects between the outputs of the two filters and thus a reconfigurable system is obtained. The switch used uses a magnetic actuation system and requires a voltage pulse of less than 4.0 V and consumes a peak transient current of 49 mA. The quiescent current consumption is 0 mA. The two passbands of the system presented here are at 1.8 GHz and 2.2 GHz. The rejection between the bands is about 20 dB. Much better rejection is possible by improving the isolation characteristic of the switch.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.232
Teacher spread0.202 · 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

Citations5
Published2005
Admission routes1
Has abstractyes

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