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Published on: November 12, 2019
Pinning synchronization of delayed neural networks
Jin Zhou1, Xiaoqun Wu, Wenwu Yu
1Department of Electronic Information Engineering, Hong Kong Polytechnic University, Hong Kong. enjzhou@polyu.edu.hk
Chaos (Woodbury, N.Y.)
|January 7, 2009
Summary
This study identifies specific neurons for adaptive pinning synchronization in delayed neural networks. Simple controllers can achieve global synchronization under mild conditions, verified with Hindmarsh-Rose neuron models.
Area of Science:
- Control theory
- Computational neuroscience
- Network dynamics
Background:
- Neural networks exhibit complex dynamics, making synchronization challenging.
- Pinning control offers a strategy to synchronize networks by controlling a subset of nodes.
- Identifying optimal nodes for control remains an open question.
Purpose of the Study:
- To determine which neurons should be controlled for adaptive pinning synchronization.
- To develop simple adaptive feedback controllers for delayed neural networks.
- To verify the proposed control strategy on a neurobiological model.
Main Methods:
- Utilizing Schur complement and Lyapunov function methods for theoretical analysis.
- Developing topology-based conditions for synchronization.
- Applying a specific pinning control technique to Hindmarsh-Rose neurons.
Main Results:
- Established that simple adaptive feedback controllers can achieve global synchronization.
- Identified mild, topology-based conditions sufficient for synchronization.
- Demonstrated the effectiveness of the control strategy through numerical simulations.
Conclusions:
- Adaptive pinning synchronization is achievable in general delayed neural networks.
- The choice of controlled neurons is crucial for efficient synchronization.
- The proposed method is effective for neurobiological network models.
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