Fractal encoding in a chaotic neural network.
Fractal encoding in a chaotic neural network.
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DOI：
10.1103/physreve.64.046202
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发表时间：
2001-09
期刊：
影响因子：
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通讯作者：
J. K. Ryeu;Kazuyuki Aihara;Ichiro Tsuda
中科院分区：
文献类型：
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作者：
J. K. Ryeu;Kazuyuki Aihara;Ichiro Tsuda
我们分析了一个由三个神经元组成的混沌神经网络模型，即一个混沌强迫神经元和两个神经元组成一个具有收缩映射特性的稳定响应系统，用于混沌动力学的数字编码。我们发现，动力学的混沌迫使神经元嵌入在一个分形吸引子的两个神经元响应系统的代码序列的形式。我们考虑了混沌强迫神经元的状态转移与收缩系统状态空间中吸引子上的层次分形结构之间的关系。我们还报告硬件实现所提出的模型与模拟电子电路调查分形吸引子的混沌神经网络作为一个现实的系统。
We analyze a model of a chaotic neural network consisting of three neurons, namely a chaotically forcing neuron and two neurons comprizing a stable response system with a contraction mapping property, for digital encoding with chaotic dynamics. We show that dynamics of the chaotically forcing neuron is embedded in the form of a code sequence on a fractal attractor of the two-neuron response system. We consider the relation between the state transition of the chaotically forcing neuron and the hierarchical fractal structure on the attractor in the state space of the contracting system. We also report hardware implementation of the presented model with an analog electronic circuit to investigate the fractal attractor of the chaotic neural network as a realistic system.