School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, Singapore, 639798, Singapore,
Cogn Neurodyn. 2007 Jun;1(2):185-8. doi: 10.1007/s11571-006-9004-7.
We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.
我们表明，通过神经网络之间的相互作用，可以有效地调整高阶二进制神经网络中的混沌和振荡。我们的结果表明，网络相互作用可能是一种有用的方法，可以用于调整使用混沌和振荡进行信息处理的系统中的动态活动水平，或者用于抑制需要稳定性的系统中的振荡行为。
