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Record W2991158361 · doi:10.1109/sielmen.2019.8905907

CSAP and TFSG – Circuit Symbolic Analysis Programs

2019· article· en· W2991158361 on OpenAlexaff
Marilena Stănculescu, Sorin Deleanu, Diana Ramona SANATESCU, Alexandra Ionescu, Atanasie Moscu, Lavinia Bobaru

Bibliographic record

Venue2019 International Conference on Electromechanical and Energy Systems (SIELMEN) · 2019
Typearticle
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsNorthern Alberta Institute of Technology
Fundersnot available
KeywordsComputer scienceSymbolic data analysisSymbolic executionProgramming languageTheoretical computer scienceSoftware

Abstract

fetched live from OpenAlex

For the symbolic, partial - symbolic and numeric generation of the transfer functions for both single-in-single-out (SISO), respectively multiple-in-multiple-out (MIMO) circuits, the initial version of the Circuit Symbolic Analysis Program (CSAP) program evolved into so-called Transfer Function Symbolic Generation (TFSG) program. Circuits analyzed via CSAP and TFSG may contain linear and nonlinear resistors, inductors, and capacitors, independent voltage, and current sources, all four types of linear controlled sources: voltage-controlled voltage source (VCVS), voltage-controlled current source (VCCS), current-controlled voltage source (CCVS), current-controlled current source (CCCS). It can also contain any multi-pol and multi-port, having an equivalent circuit made up of only two-terminal electrical elements alongside the controlled sources. Furthermore, we proved that both CSAP and TFSG are handy tools for analysis and design of the nonlinear time-invariant analog circuits because we can keep as the symbols only parameters associated with these circuit elements. The work concludes with some illustrative examples.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.847

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 head0.014
GPT teacher head0.210
Teacher spread0.196 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2019
Admission routes1
Has abstractyes

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