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Record W4402474358 · doi:10.1109/tcsii.2024.3459091

Closed-Form Expressions for the Input Impedance of Some 2-D Fractal Circuit Networks

2024· article· en· W4402474358 on OpenAlexaff
Ahmed S. Elwakil, Anis Allagui, Mohamed B. Elamien, Costas Psychalinos, Brent Maundy

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2024
Typearticle
Languageen
FieldComputer Science
TopicNeural Networks and Applications
Canadian institutionsUniversity of CalgaryMcMaster University
Fundersnot available
KeywordsFractalElectrical impedanceMathematicsTopology (electrical circuits)Computer scienceMathematical analysisElectrical engineeringEngineeringCombinatorics

Abstract

fetched live from OpenAlex

We derive closed form expressions for the input impedance of two-dimensional (2-D) infinite ladder-tree and tree-ladder networks using the combination of results for the input impedance of an infinite 1-D ladder network and an infinite 1-D tree network. We show that the effect of the number of branches in the tree network can always be absorbed via impedance scaling resulting in a universal formula derived in this brief. The meaningful number of branches of the tree network is shown to be either two branches; i.e., a binary tree, or four branches; i.e., a quaternary tree. Special cases of component choices are investigated, and both circuit simulations and experimental results are provided to validate the theory.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
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
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.258
Teacher spread0.233 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations2
Published2024
Admission routes1
Has abstractyes

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