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Record W2541442902 · doi:10.1109/icece.2006.355675

Application of the Wavelet Packet Transform for the Identification of Chaotic Signals in the Current-Programmed DC/DC Boost Converters

2006· article· en· W2541442902 on OpenAlexaff
M. A. S. K. Khan, Md. Azizur Rahman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicChaos control and synchronization
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWavelet packet decompositionWaveletConvertersChaoticDiscrete wavelet transformWavelet transformElectronic engineeringComputer scienceStationary wavelet transformHarmonicWaveformSecond-generation wavelet transformBoost converterControl theory (sociology)EngineeringPhysicsVoltageTelecommunicationsElectrical engineeringArtificial intelligenceAcoustics

Abstract

fetched live from OpenAlex

The wavelet packet transform (WPT), a digital realization of the wavelet transform (WT), has been used in this work for identifying and characterizing sub-harmonic and chaotic signals in a current-mode-controlled boost converter. The operation of the boost converter under current-programmed control is explained, and some computer-generated waveforms are presented in order to illustrate the various possible operating regimes of the current-programmed dc/dc converters. Samples of the state variables of different periodic and chaotic operating conditions of the converter are decomposed up to a certain level of resolution of the wavelet packet tree using a selected mother wavelet in order to characterize different sub-harmonic and chaotic signals occurred in the converter. The wavelet-transformed coefficients of the sampled state variables of different frequency sub bands of the wavelet packet tree are able to differentiate effectively between different periodic and chaotic operating conditions of the converter.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.164

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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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 designOther design
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

Citations0
Published2006
Admission routes1
Has abstractyes

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