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Record W2148600772 · doi:10.1109/iscas.1999.777618

Distortion analysis of periodically switched nonlinear circuits

2003· article· en· W2148600772 on OpenAlexaff
Fei Yuan, A. Opal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicControl Systems and Identification
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIntermodulationSpiceDistortion (music)Volterra seriesTotal harmonic distortionElectronic circuitNonlinear distortionNonlinear systemComputer scienceFrequency domainElectronic engineeringEngineeringVoltagePhysicsElectrical engineeringCMOSAmplifier

Abstract

fetched live from OpenAlex

This paper presents a Volterra series-based frequency-domain method for small-signal distortion analysis of general periodically switched nonlinear (PSN) circuits. Both harmonic and intermodulation distortion are investigated. It is shown that the behavior of PSN circuits can be characterized by a set of intrinsically related periodically switched linear (PSL) circuits. The proposed method has been implemented in a computer program. Numerical results computed using the proposed method are compared with those from SPICE simulation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.008
GPT teacher head0.199
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2003
Admission routes1
Has abstractyes

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