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Record W979056606 · doi:10.5815/ijwmt.2015.01.01

Matlab-Based Computer-Aided-Design Algorithm for Designing Stepped-Impedance Resonator Low-Pass Filters in Microstrip Technology

2015· article· en· W979056606 on OpenAlexaff
Luv Tomar, Saurabh Gupta, Raghuvir Singh Tomar, P. Bhartia

Bibliographic record

VenueInternational Journal of Wireless and Microwave Technologies · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsCarleton University
Fundersnot available
KeywordsHFSSMATLABMicrostripComputationResonatorElectronic engineeringElectrical impedanceFilter (signal processing)CADComputer scienceLow-pass filterAlgorithmEngineeringElectrical engineeringEngineering drawingTelecommunicationsMicrostrip antenna

Abstract

fetched live from OpenAlex

An accurate MATLAB-based CAD algorithm for quickly designing microstrip-based stepped-impedance resonator (SIR) low-pass filter is reported. The algorithm uses a circuit-theory approach to implement speedy computations, compared to the time-consuming computations involved in using electromagnetic theory. The accuracy of the proposed algorithm is verified for two widely-different practical examples in the 0-4GHz frequency range, against results obtained using Ansoft/Ansys circuit simulation tool, and against results obtained using the 3D electromagnetic simulator HFSS. The agreement among the three sets of data is seen to be excellent for most cases, and is found to be practically acceptable in the worst-case.

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.579
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.234
Teacher spread0.218 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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