Coherent Response in a Chaotic Neural Network
Coherent Response in a Chaotic Neural Network
复制标题
混沌神经网络中的相干响应
DOI：
10.1023/a:1009626028831
复制
发表时间：
2000
影响因子：
3.1
通讯作者：
K. Aihara
中科院分区：
文献类型：
--
作者：
H. Nishimura;N. Katada;K. Aihara
建立了耦合常数对应于一定信息的混沌神经网络的信号驱动方案，研究了其确定性动力学下的类随机共振效应，并与传统的含随机噪声的Hopfield网络进行了比较.结果表明，混沌神经网络可以增强弱阈下信号，并具有更高的一致性之间的刺激和响应的能力比传统的随机模型所获得的。
We set up a signal-driven scheme of the chaotic neural network with the coupling constants corresponding to certain information, and investigate the stochastic resonance-like effects under its deterministic dynamics, comparing with the conventional case of Hopfield network with stochastic noise. It is shown that the chaotic neural network can enhance weak subthreshold signals and have higher coherence abilities between stimulus and response than those attained by the conventional stochastic model.