Boui A Boya Bertrand Frederick, Tabekoueng Njitacke Zeric, Telem Adelaide Nicole Kengnou, Kengne Jacques
Unité de Recherche d'Automatique et d'Informatique Appliquée (UR-AIA), IUT-FV Bandjoun University of Dschang, P.O. Box 134, Bandjoun, Cameroon.
Institute of Computer Technology and Information Security, Engineering and Technological Academy, Southern Federal University, P.O. Box 347900, Taganrog, Russia.
Heliyon. 2024 Dec 27;11(1):e41526. doi: 10.1016/j.heliyon.2024.e41526. eCollection 2025 Jan 15.
This study presents a family of coexisting multi-scroll chaos in a network of coupled non-oscillatory neurons. The dynamics of the system are analyzed using phase portraits, basins of attraction, time series, bifurcation diagrams, and spectra of Lyapunov exponents. The coexistence of multiple bifurcation diagrams leads to a complex pattern of multi-scroll formation, which is further complicated by the presence of coexisting single-scroll attractors that merge to form multi-scroll chaos. In addition, the presence of bursting phenomena and multiple firing partners is present in the model. A control strategy based on a noninvasive control method is applied to select the desired multi-scroll. The effectiveness of the control method is demonstrated through numerical simulations. The experimental validation on an Arduino microcontroller confirms the theoretical results and demonstrates the feasibility of implementing the proposed model. These remarkable behaviors hold significant implications for understanding brain dynamics and have potential applications in various fields.
本研究展示了耦合非振荡神经元网络中一族共存的多涡卷混沌。使用相图、吸引域、时间序列、分岔图和李雅普诺夫指数谱对系统动力学进行了分析。多个分岔图的共存导致了复杂的多涡卷形成模式，而共存的单涡卷吸引子合并形成多涡卷混沌则进一步使情况变得复杂。此外，模型中还存在爆发现象和多个激发伙伴。应用基于非侵入性控制方法的控制策略来选择所需的多涡卷。通过数值模拟证明了控制方法的有效性。在Arduino微控制器上的实验验证证实了理论结果，并证明了实现所提出模型的可行性。这些显著行为对于理解脑动力学具有重要意义，并在各个领域具有潜在应用。
