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A Transmisson Line Approach to Reduce Transition Sensitivity of a Filter Package on High Density PCB

2023· article· en· W4408717175 on OpenAlexaff
Mehdi Hosseini, Iftikhar Ahmed, Mehdi Dadgarpour, Nima Javanbakht, Rajni Pagoti, Keith Heggie, Mike Cooper

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsCMC Microsystems (Canada)
Fundersnot available
KeywordsSensitivity (control systems)Line (geometry)Filter (signal processing)Computer scienceElectronic engineeringEngineeringMathematicsComputer vision

Abstract

fetched live from OpenAlex

A transmission line based approach to improve transition sensitivity of filter packages on a high density printed circuit board (PCB) is proposed. It is useful for optimization and analysis of high frequency components on a substrate throughout design and simulation stages of a microwave system. For validation of the approach, a compact surface-mount filter package with very high rejection band is simulated and analyzed on a PCB. The concept of the work is simple yet an interesting RF design technique, which can enhance or maintain the performance of filters in desired frequency bands. Although the approach is applied to a particular component for demonstration, it can streamline the selection of various commercial discrete filters.

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 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 score0.161
Threshold uncertainty score0.549

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 integrity0.0000.000
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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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