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Using Neuron Spiking Activity to Trigger Closed-Loop Stimuli in Neurophysiological Experiments
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Adaptive Event-Triggered Synchronization of Reaction-Diffusion Neural Networks
IEEE Transactions on Neural Networks and Learning Systems
|October 15, 2020
Summary
This study introduces an adaptive event-triggered sampled-data control (ETSDC) for synchronizing reaction-diffusion neural networks (RDNNs) with delays. The adaptive mechanism efficiently conserves communication resources by adjusting thresholds dynamically.
Area of Science:
- Control Systems Engineering
- Computational Neuroscience
- Network Synchronization
Background:
- Reaction-diffusion neural networks (RDNNs) are crucial for modeling complex spatio-temporal dynamics.
- Synchronization of RDNNs is essential for information processing and pattern recognition.
- Existing event-triggered control schemes often use fixed thresholds, limiting resource efficiency.
Purpose of the Study:
- To design an adaptive event-triggered sampled-data control (ETSDC) mechanism for synchronizing RDNNs.
- To address random time-varying delays in RDNNs.
- To enhance communication resource efficiency in control systems.
Main Methods:
- Development of an adaptive ETSDC mechanism with dynamically adjusted thresholds.
- Incorporation of probabilistic random time-varying delays within two intervals.
- Construction of a Lyapunov-Krasovskii functional (LKF) for stability analysis.
- Derivation of new synchronization criteria using linear matrix inequalities (LMIs).
Main Results:
- The proposed adaptive ETSDC mechanism effectively synchronizes RDNNs with random delays.
- The adaptive threshold adjustment significantly conserves communication bandwidth.
- New, robust synchronization criteria were derived and validated.
- The control gain was successfully obtained by solving LMIs.
Conclusions:
- The adaptive ETSDC strategy offers superior communication efficiency compared to traditional methods.
- The developed synchronization criteria are effective for RDNNs with complex delay characteristics.
- Numerical simulations confirm the efficacy and advantages of the proposed control scheme.
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