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Record W1992502989 · doi:10.1109/rws.2010.5434107

Multiport interferometer techniques for innovative transceiver applications

2010· article· en· W1992502989 on OpenAlexaff
Ke Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversité de MontréalPolytechnique Montréal
Fundersnot available
KeywordsTransceiverElectronic engineeringComputer scienceWidebandRadarCognitive radioMicrowavePhotonicsElectronic circuitInterferometryElectrical engineeringTelecommunicationsEngineeringPhysicsCMOSWireless

Abstract

fetched live from OpenAlex

This paper presents and reviews basic concepts and emerging development of our proposed multi-port interferometer techniques and demonstrates their applications in the design of carrier-based, impulse ultra-wideband and cognitive transceivers at microwave and millimeter-wave frequencies. Such innovative techniques can be extended to the design of transceivers over terahertz and optical ranges. Various architectures of multiport circuits are discussed with respect to different applications. Practical implementations under different technological platforms are described with simulated and measured results for QAM, UWB and tunable multiband applications. In particular, the equivalence between the multiport junction and mixing circuit is highlighted with respect to the concept of interferometers for direct frequency conversion and translation. It is shown that such multiport techniques are very promising and flexible for the low-cost design of integrated microwave, millimeter-wave and photonic systems such as software-defined radio, cognitive radio and radar systems as well as photonic transceivers.

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

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