Stability, control and synchronization of uncertain fractional order physiological networks

Stability, regulation, and synchronization of unknown fractional order (FO) brain networks and physiological networks are the main areas of study. In the modeling and control of complex dynamic systems, such as mechanical, chemical, biological, and electrical systems, neural networks have grown in importance. Nonetheless, these networks' synchronization, stability, and control continue to be major obstacles. These difficulties are exacerbated by chaotic physiological networks, which stand in for chaotic nodes in physical systems like biological brain systems and solid-state devices. In order to properly manage these intricate systems, recent research has shown that novel control and synchronization techniques are required. Despite progress, there are still unanswered questions about the chaotic behaviors and topological ambiguities in these networks, which calls for more research.

The primary focus is on the stability, regulation, and synchronization of physiological and unknown fractional order (FO) brain networks. Neural networks have become increasingly important in the modeling and control of complex dynamic systems, including electrical, mechanical, chemical, and biological systems. However, synchronization, control, and stability remain significant challenges for these networks. Chaotic physiological networks, which represent chaotic nodes in physical systems such as solid-state devices and biological brain systems, make these challenges worse. Recent studies have demonstrated the need for new control and synchronization strategies to effectively manage these complex systems. More research is necessary because, despite advancements, there are still unresolved issues regarding the chaotic behaviors and topological ambiguities in these networks.

To gather further insights into the stability, control, and synchronization of uncertain fractional order neural networks and physiological networks, we welcome articles addressing, but not limited to, the following themes:
- Stability of FO uncertain neural networks
- Stability of FO uncertain physiological networks
- Synchronization of coupled FO uncertain physiological networks
- Control of FO uncertain physiological networks
- FO Neural Control for robotic systems
- Synchronization of biological FO uncertain physiological networks
- Synchronization of FO uncertain complex neural networks
- Synchronization of quaternion neural networks
- FO uncertain neural control for electrical and power systems
- Topological analysis of uncertainties found in these systems
- Robustness analysis
- Bifurcations of complex chaotic neural networks and other types of physiological networks

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
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Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Network physiology, neural networks, Stability, Synchronization, stabilization, control, chaotic complex networks, Fractional order calculus

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