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Record W4220988501 · doi:10.1088/1674-1056/ac5e95

Memristor hyperchaos in a generalized Kolmogorov-type system with extreme multistability

2022· article· en· W4220988501 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

VenueChinese Physics B · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsYork University
Fundersnot available
KeywordsMultistabilityMemristorComputer scienceChaoticBistabilityBifurcation diagramTopology (electrical circuits)Control theory (sociology)BifurcationStatistical physicsApplied mathematicsPhysicsMathematicsArtificial intelligenceNonlinear systemQuantum mechanics

Abstract

fetched live from OpenAlex

Memristor chaotic systems have aroused great attention in recent years with their potentials expected in engineering applications. In this paper, a five-dimension (5D) double-memristor hyperchaotic system (DMHS) is modeled by introducing two active magnetron memristor models into the Kolmogorov-type formula. The boundness condition of the proposed hyperchaotic system is proved. Coexisting bifurcation diagram and numerical verification explain the bistability. The rich dynamics of the system are demonstrated by the dynamic evolution map and the basin. The simulation results reveal the existence of transient hyperchaos and hidden extreme multistability in the presented DMHS. The NIST tests show that the generated signal sequence is highly random, which is feasible for encryption purposes. Furthermore, the system is implemented based on a FPGA experimental platform, which benefits the further applications of the proposed hyperchaos.

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 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 score0.055
Threshold uncertainty score0.631

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 head0.023
GPT teacher head0.224
Teacher spread0.200 · 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