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Record W2140235536 · doi:10.1109/eumc.2007.4405246

A miniature LTCC bandpass filter using novel resonators for GPS applications

2007· article· en· W2140235536 on OpenAlexaff
G. Brzezina, Langis Roy, Leonard MacEachern

Bibliographic record

Venue2007 European Microwave Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsCarleton University
Fundersnot available
KeywordsBand-pass filterCapacitorResonatorElectronic engineeringInductorMaterials scienceElectronic filter topologyBandwidth (computing)Prototype filterFilter (signal processing)OptoelectronicsElectrical engineeringComputer scienceEngineeringLow-pass filterTelecommunications

Abstract

fetched live from OpenAlex

We present a novel bandpass filter embedded in a low-temperature co-fired ceramic (LTCC) package designed for small size and robustness. Given the three-dimensional packaging capability of the LTCC substrate, the multilayer resonators are integrated into the module - eliminating the need for their discrete versions. The resonators are comprised of high Q spiral inductors that are combined with four layer parallel plate capacitors. The novel topology of placing the capacitor in the centre and two layers below the plane of the inductor allows for simultaneous area and performance optimization. The complete LTCC bandpass filter module measures only 5 mm times 5.4 mm times 0.8 mm. This version of the design utilizes discrete coupling capacitors to minimize size. The simulation results show the filter to have a centre frequency of 1.525 GHz and a bandwidth of 128 MHz. This is believed to be the smallest implementation of a LTCC bandpass filter for GPS applications.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.241
Teacher spread0.212 · 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

Citations17
Published2007
Admission routes1
Has abstractyes

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