Stability and Spatiotemporal Bifurcations in Spatially Distributed Neural Networks with Nonlocal Delay

Stability and Spatiotemporal Bifurcations in Spatially Distributed Neural Networks with Nonlocal Delay
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具有非局部延迟的空间分布式神经网络的稳定性和时空分岔

DOI:
10.1515/zna-2018-0116
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发表时间:
2018-07
期刊:
Zeitschrift für Naturforschung A
影响因子:
--
通讯作者:
Juncheng Jiang
Juncheng Jiang
中科院分区:
其他
文献类型:
--
作者:
Yanqiu Li;Juncheng Jiang

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摘要研究了具有非局部时滞的实直线上神经网络平衡点和分岔的稳定性。线性部分给出了稳定平衡的充分条件。特征值分析暗示了分岔的存在,并利用神经网络中典型的兴奋性和抑制性连接核,根据不同的情况讨论了可能的分岔。用多尺度方法研究分岔行波或点的稳定性是一种有利的工具。为了说明我们的理论,研究了贝壳连续时间圆形掩模模型的动力学。研究表明,活动功能的形状和范围以及突触的权重都能影响模型的动力学特性。最后,用数值方法揭示了贝壳模型的分岔集和分岔模式的多样性。
Abstract The stability of equilibria and bifurcations of neural networks in a real line with nonlocal delay are presented. A sufficient condition of stable equilibria is declared by the linear part. Eigenvalue analysis implies the existence of bifurcations, and by exploiting typical excitatory and inhibitory connectivity kernels in a neural network, the possible bifurcations are discussed according to various cases. It is an advantageous tool using a multiple-scale method to study the stability of bifurcated travelling waves or spots. As an illustration of our theory, the dynamics of a seashell continuous-time circular mask model are investigated. It is shown that both the shape and range of active function and synaptic weights can affect the dynamics of the model. Finally, the bifurcation set and the variety of bifurcated patterns of the seashell model are numerically revealed.
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