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Novel Adaptive Strategies for Synchronization of Linearly Coupled Neural Networks With Reaction-Diffusion Terms

机译:具有反应扩散项的线性耦合神经网络同步的新自适应策略

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摘要

In this paper, two types of linearly coupled neural networks with reaction-diffusion terms are proposed. We respectively investigate the adaptive synchronization of these two types of complex network models. With local information of node dynamics, some novel adaptive strategies to tune the coupling strengths among network nodes are designed. By constructing appropriate Lyapunov functionals and using inequality techniques, several sufficient conditions are given for reaching synchronization by using the designed adaptive laws. Finally, two examples with numerical simulations are provided to demonstrate the effectiveness of the theoretical results.
机译:本文提出了两种类型的具有反应扩散项的线性耦合神经网络。我们分别研究了这两种类型的复杂网络模型的自适应同步。利用节点动力学的局部信息,设计了一些新颖的自适应策略来调整网络节点之间的耦合强度。通过构造适当的Lyapunov函数并使用不等式技术,使用设计的自适应定律给出了几个足以达到同步的条件。最后,提供了两个带有数值模拟的例子来证明理论结果的有效性。

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