Chaotic Stationary Solutions of Cellular Neural Networks
Chaotic Stationary Solutions of Cellular Neural Networks
复制标题
细胞神经网络的混沌平稳解
DOI：
10.1142/s0218127403008612
复制
发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Zengrong Liu
中科院分区：
文献类型：
--
作者：
Fang;Zengrong Liu
本研究通过应用迭代映射方法描述了无特定项输入的一维细胞神经网络 (CNN) 的混沌平稳解。在完美确定的特定参数下，对应于CNN平稳解的映射是二维的，并且具有双曲不变康托集，在该映射上与符号空间的两侧平移拓扑共轭。使用的主要工具是康利-莫泽条件。
This study describes the chaotic stationary solutions of one-dimensional Cellular Neural Networks (CNN) without inputs with a specific term by applying the iteration map method. Under perfectly determined specific parameters, the map which corresponds to the stationary solution of CNN is two-dimensional and has a hyperbolic invariant Cantor set on which it is topologically conjugate to a two-sided shift of symbols space. The used main tool is the Conley–Moser conditions.