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Record W4407914858 · doi:10.23977/jeis.2025.100104

Research on the Stability of Nonlinear Oscillator Systems Based on Time Delay Coupling

2025· article· en· W4407914858 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Electronics and Information Science · 2025
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsnot available
FundersEducation Department of Jiangxi Province
KeywordsNonlinear systemStability (learning theory)Coupling (piping)Control theory (sociology)Computer sciencePhysicsMaterials scienceQuantum mechanicsArtificial intelligence

Abstract

fetched live from OpenAlex

In the field of contemporary physics and engineering, the study of nonlinear oscillator systems has important theoretical significance and broad application prospects. Among them, nonlinear oscillator systems with time delay effects have received widespread attention due to their unique multi-steady state, chaos, and complex periodic motion. This paper aims to conduct in-depth research on nonlinear oscillator systems with delay effects, revealing their complex motion patterns and the essence of their mutual influence. This paper aims to model nonlinear systems with time delay effects. Using a combination of numerical simulation and theoretical analysis, its dynamic characteristics under different working conditions are explored. The dynamic behavior of the system is studied using phase diagrams and Lyapunov exponents. On this basis, representative periodic and chaotic movements are identified by systematically scanning its parameter space. In the case of the Lyapunov exponent (λ<0), the system was stable; when λ approached 0, the system reached a critical steady state. The research results of the paper provide new ideas and experimental methods for the study of delay coupling systems, as well as new ideas and methods for the design and optimization of such systems.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.278
Teacher spread0.265 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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