Scholarlink

<p>This study intricately examines the dynamic interplay between two captivating phenomena: strange non-chaotic attractors (SNAs) and chimera states. By examining a Chay neuronal system with an added quasi-periodic force, the research aims to elucidate the underlying mechanisms governing their relationship. The system displays a wide variety of attractor states, from periodic and unusual non-chaotic to chaotic, when a control parameter is tuned precisely. The trajectories and dynamics of the system can be visually represented by phase portraits, Lyapunov exponents, and bifurcation plots. To understand the intricate behaviour of the system, the study examines transitions between various attractors by employing methods including power spectrum analysis, finite-time Lyapunov exponents, and singular continuous spectrum patterns. Rigorous analysis confirms various chimera states, including incoherent oscillations, spatially synchronized patterns, multi-headed chimeras, and imperfect chimera states. The coexistence of SNA and chimera states brings a unique combination of robust quasi-periodic complexity and spatially structured coherence and incoherence. It introduces a type of dynamical behavior where complex, nonchaotic patterns emerge in a spatially structured way, potentially providing new avenues for neural computation and robust pattern generation in both artificial and biological systems.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Exploring nonchaotic dynamics and synchronization in externally stimulated Chay neuronal networks

  • 期刊论文

  • 发表日期：

    2025年9月25日

查看全文
  • A. Prasina,
  • V. Samuthira Pandi,
  • R. Shalinirajan,
  • M. Rajasekaran,
  • E. Gurumoorthi,
  • S. Ramkumar

摘要

This study intricately examines the dynamic interplay between two captivating phenomena: strange non-chaotic attractors (SNAs) and chimera states. By examining a Chay neuronal system with an added quasi-periodic force, the research aims to elucidate the underlying mechanisms governing their relationship. The system displays a wide variety of attractor states, from periodic and unusual non-chaotic to chaotic, when a control parameter is tuned precisely. The trajectories and dynamics of the system can be visually represented by phase portraits, Lyapunov exponents, and bifurcation plots. To understand the intricate behaviour of the system, the study examines transitions between various attractors by employing methods including power spectrum analysis, finite-time Lyapunov exponents, and singular continuous spectrum patterns. Rigorous analysis confirms various chimera states, including incoherent oscillations, spatially synchronized patterns, multi-headed chimeras, and imperfect chimera states. The coexistence of SNA and chimera states brings a unique combination of robust quasi-periodic complexity and spatially structured coherence and incoherence. It introduces a type of dynamical behavior where complex, nonchaotic patterns emerge in a spatially structured way, potentially providing new avenues for neural computation and robust pattern generation in both artificial and biological systems.