MétaCan
Menu
Back to cohort
Record W2100754171 · doi:10.1109/tmtt.2004.837201

A Space-Mapping Design Framework

2004· article· en· W2100754171 on OpenAlexaff
J.W. Bandler, Qingsha S. Cheng, Daniel M. Hailu, Natalia K. Nikolova

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2004
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSpace mappingHFSSComputer scienceResidualTransformerMicrowave engineeringMicrowaveSoftwareImplementationWaveguide filterElectronic engineeringComputer engineeringIterative designEngineering drawingFilter (signal processing)AlgorithmFilter designProgramming languageEngineeringPrototype filterMathematical optimizationElectrical engineeringMathematicsTelecommunications

Abstract

fetched live from OpenAlex

We present a comprehensive microwave design framework for implementing the original, aggressive, implicit, and response residual space-mapping (SM) approaches through widely available software. General steps and tools for possible SM implementations are elaborated. Our presentation is a reference guide for microwave designers using the SM technique. An instructive "multiple cheese-cutting" example demonstrates the SM approach to engineering design and some possible pitfalls. For the first time, an ADS framework implements the SM steps interactively. A three-section transformer example illustrates the approach, step by step. A six-section H-plane waveguide filter design emerges after four iterations, using the implicit SM and the response-residual space-mapping (RRSM) optimization entirely within the design framework. An RRSM surrogate is developed to match the fine (HFSS) model. We use sparse frequency sweeps and do not require Jacobians of the fine model.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.012
GPT teacher head0.218
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
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

Citations46
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Microwave Theory and TechniquesSame topicMicrowave Engineering and WaveguidesFrench-language works237,207