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Record W2117091628 · doi:10.1109/tmtt.2010.2086471

Enhanced Microwave Multiplexing Network

2010· article· en· W2117091628 on OpenAlexaff
Ming Yu, Ying Wang

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsOntario Tech UniversityCOM DEV International
Fundersnot available
KeywordsMultiplexerMultiplexingPassbandElectronic engineeringMicrowaveComputer scienceChannel (broadcasting)ResonatorFrequency-division multiplexingStatistical time division multiplexingTransmission (telecommunications)Filter (signal processing)Communications satelliteComputer networkOrthogonal frequency-division multiplexingEngineeringElectrical engineeringTelecommunicationsBand-pass filterSatellite

Abstract

fetched live from OpenAlex

A new approach for designing a microwave multiplexing network is presented in order to improve channel performance. Through design and optimization of the connecting transmission line structure, the new approach ensures that an extra pole is formed in the passband of each channel. The channel filter order is therefore increased by one without additional resonators. Significant improvement in the performance of the multiplexer is achieved without the penalty of increased size or weight of the hardware, which is extremely important for applications in communication satellite. Simulation and measurement results are used to demonstrate the feasibility of such enhanced microwave multiplexing networks.

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)0.001
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: none
Teacher disagreement score0.798
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

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