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Record W2394942100 · doi:10.1049/iet-cds.2015.0226

Periodic switching circuit analysis using admittance matrices

2016· article· en· W2394942100 on OpenAlex
Peter Pawliuk, K. Nickerson

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

VenueIET Circuits Devices & Systems · 2016
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsBlackberry (Canada)
Fundersnot available
KeywordsAdmittanceAdmittance parametersFrequency domainElectrical impedanceElectronic circuitFrequency responseImpedance parametersRadio frequencyVoltageEquivalent circuitTime domainMatrix (chemical analysis)Electronic engineeringTopology (electrical circuits)Computer scienceMathematicsElectrical engineeringEngineeringMathematical analysisMaterials scienceTelecommunications

Abstract

fetched live from OpenAlex

Radio‐frequency (RF) circuits employing periodically gated switches can be difficult to characterise in the frequency domain because they are time variant. The time variance causes frequency mixing and makes impedances difficult to define. A new method of frequency‐domain analysis for periodic switching circuits is proposed in which a switch is represented by a matrix of admittance values. The columns of the admittance matrix correspond to voltage frequencies and the rows correspond to current frequencies, facilitating frequency translation effects in the circuit. The frequency domain is considered using a discretised set of harmonically related frequencies. The method is applied to the design and analysis of an RF switching mixer to demonstrate its advantages in calculating impedances and tuning the frequency response.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.650
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.233
Teacher spread0.209 · 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