MétaCan
Menu
Back to cohort
Record W3176877422 · doi:10.1109/tcad.2021.3093016

An Efficient EM-Based Synthesis Technique for Single-Band and Dual-Band Waveguide Filters

2021· article· en· W3176877422 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPrototype filterFilter (signal processing)Waveguide filterm-derived filterFilter designComputer scienceNetwork synthesis filtersMulti-band deviceElectronic engineeringDual (grammatical number)Band-pass filterConstant k filterIdeal (ethics)Electronic filter topologyTopology (electrical circuits)TelecommunicationsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

This article presents a systematic and an efficient synthesis technique for designing single-band and dual-band waveguide (WG) filters with transmission zeros (TZs). The proposed electro-magnetic (EM)-based synthesis technique directly results in a filter design with an RF performance that is in excellent agreement with the ideal filter performance, thus significantly reducing the post fine optimization effort. Furthermore, the proposed technique also reduces the EM simulation resources required for the filter synthesis. The synthesis technique is lucidly explained by designing a symmetrical 6th-order WG filter with four TZs, a 9th-order filter with three asymmetric TZs and a 6th-order dual-band filter. To the best of the author’s knowledge, this is the first filter synthesis technique, which can be adopted to design WG filters, including TZs with minimum or no post fine optimization.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.025
GPT teacher head0.214
Teacher spread0.189 · 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