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Record W2289039579 · doi:10.1109/nemo.2015.7415098

Time-invariant behavioral modeling for harmonic balance simulation based on waveform shape maps

2015· article· en· W2289039579 on OpenAlexaff
Amir-Reza Amini, Slim Boumaiza

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHarmonic balanceWaveformNonlinear systemBehavioral modelingControl theory (sociology)Invariant (physics)Representation (politics)Nonlinear distortionDiscrete time and continuous timeFrequency domainComputer scienceTime domainTotal harmonic distortionAlgorithmMathematicsEngineeringArtificial intelligencePhysicsVoltageTelecommunications

Abstract

fetched live from OpenAlex

A new time-domain time-invariant periodic nonlinear behavioral model for multi-port systems is formulated from first principles in this paper. Unlike frequency-domain behavioral models like the Poly-Harmonic Distortion (PHD) model that describe the output frequency spectral components of the system, this black-box approach provides a time-invariant map of the discrete-time representation of the input waveform shape to the discrete-time representation of the output waveform shape, resulting in a reduction of the number of describing functions compared to a frequency domain description of the system. A two-port transistor behavioural model implementation for harmonic balance simulation is presented. The validation results show that the proposed model is capable of modeling the steady-state periodic output of multi-port nonlinear time-invariant systems and has potential to assist in the computer-aided design of RF systems with nonlinear components.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.785

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 head0.066
GPT teacher head0.273
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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2015
Admission routes1
Has abstractyes

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