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Record W2146551446 · doi:10.1109/tcsi.2008.916434

Gain Scheduling Synchronization Method for Quadratic Chaotic Systems

2008· article· en· W2146551446 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicChaos control and synchronization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSynchronization of chaosSynchronization (alternating current)Quadratic equationChaoticControl theory (sociology)Lorenz systemMathematicsBounded functionLyapunov stabilityComputer scienceScheduling (production processes)Nonlinear systemApplied mathematicsMathematical optimizationTopology (electrical circuits)Mathematical analysisPhysics

Abstract

fetched live from OpenAlex

A global gain scheduling synchronization method is developed in this paper for the identical synchronization of quadratic chaotic systems. The quadratic chaotic system contains nonlinearity of quadratic terms of system's states. With chaotic states being bounded in certain regions, the quadratic chaotic system can be rewritten into the linear parameter varying (LPV) form through algebraic transformations. Then, using the gain scheduling technique, two different synchronization structures are proposed to achieve the global synchronization for the quadratic chaotic system. The convergence of the synchronization errors is guaranteed under the second Lyapunov stability theory. Generalized Lorenz systems, such as the Chen system and the Lorenz system, are illustrated as examples to demonstrate the efficiency of the proposed methods.

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.

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 score0.984
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
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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