PWC Lorenz–Rabinovich system: complex dynamics, circuit realization, and a new technique for adaptive synchronization via sliding mode control with application to cryptosystems design
Bibliographic record
Abstract
Abstract The development of novel models can lead to new findings, design new algorithms, and expand practical applications. In this article, we propose a new piecewise-continuous (PWC) system by introducing a threshold level for the states in both the Lorenz and Rabinovich systems. This threshold enables dynamical transitions between the Lorenz system and the Rabinovich system while preserving their fundamental characteristics. Further, this new system exhibits unique dynamic behaviors, including the simultaneous presence of a self-excited chaotic set and two-point attractors, the coexistence of self-excited and hidden attractors with distinct four wings, as well as the coexistence of two hidden scrolls and hidden chaotic attractors. Moreover, the electronic circuit using off-the-shelf components is designed on a schematic capture and SPICE simulator tool. A technique for achieving adaptive synchronization (AS) between switching dynamical systems with completely unknown parameters is proposed, employing sliding mode control. Numerical simulations are conducted to validate the reliability of the AS algorithm. Furthermore, by capitalizing on the inherent switching property of PWC systems, a technique for secure communications is proposed. The approach is based on the concept of dividing the message signal into segments and distributing them across a PWC chaotic system. Subsequently, these encrypted signals are transmitted through two channels. This methodology significantly enhances the overall security of the communication. Various statistical tests are conducted to evaluate the robustness of the method.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".