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Record W2115210610 · doi:10.1109/map.2003.1203115

Visualization cf radiation-pattern characteristics of phased arrays using digital phase shifters

2003· article· en· W2115210610 on OpenAlexaff
Michel Clénet, G.A. Morin

Bibliographic record

VenueIEEE Antennas and Propagation Magazine · 2003
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsPhased arrayDirectivityElectronic engineeringQuantization (signal processing)Antenna arrayComputer sciencePhased-array opticsMATLABPhase (matter)Factor (programming language)Antenna (radio)EngineeringAlgorithmTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

This article presents graphical investigations of the array factor of phased arrays with digital phase shifters. A software program, based on basic antenna array theory, has been developed in MATLAB to obtain the main array characteristics (array factor and directivity). The array factors of linear arrays of different sizes with different types of phase shifters have been studied as a function of the number of bits and the frequency. Unconventional two-dimensional color graphical representations are used to identify some characteristics of the array factor of arrays with digital phase shifters that can not be so clearly and quickly visualized with conventional graphical representations. In particular, the effects of quantization on the array factor for arrays of different sizes and for phase shifters with different numbers of bits, over scanning, and frequency ranges, are shown using this representation. Numerous data are also provided.

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)0.002
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.249
Teacher spread0.233 · 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

Citations22
Published2003
Admission routes1
Has abstractyes

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