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Record W2477123740 · doi:10.1109/tap.2016.2594056

Design of a UWB Reflectarray as an Impedance Surface Using Bessel Filters

2016· article· en· W2477123740 on OpenAlexafffund
Liang Liang, Sean V. Hum

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Toronto
FundersOntario Ministry of Economic Development and Innovation
KeywordsPassbandBessel functionBessel filterOpticsBandwidth (computing)WidebandGroup delay and phase delayMaterials scienceAcousticsElectronic engineeringBand-pass filterPhysicsComputer scienceEngineeringTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

This paper develops a framework for designing wideband reflectarray antennas. The proposed reflectarray is implemented as a scalar impedance surface composed of subwavelength elements, whose response is designed to realize a Bessel filter response. The underlying unit cells therefore have maximum group delay bandwidth with no group delay ripples in the passband. It is shown that the reflectarrays designed using this Bessel filter approach exhibit wide bandwidth only limited by the order of the filter used to realize the Bessel filter. Simulated and measured antenna characteristics of the proposed reflectarray are presented for a C-/X-band reflectarray design. It is shown to have good beam characteristics and ultra-low temporal dispersion from 5 to 10 GHz, two attractive qualities accomplished simultaneously by the proposed reflectarray.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0010.000
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 head0.035
GPT teacher head0.269
Teacher spread0.234 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations30
Published2016
Admission routes2
Has abstractyes

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