用于信息处理的延时混沌神经网络

Time-delay chaotic neural network for information processing

为了提高混沌神经网络用于信息处理的能力,采用一种参数调节控制方法,通过对一种延时对称全局耦合混沌神经网络的黏合参数的控制研究了网络的动态联想记忆,使被控网络在仅有部分神经元进入周期态的情况下达到输出稳定,并且稳定输出序列只包含与输入模式相关的存储模式及其相反模式。仿真实验说明网络具有良好的容错能力和很高的回忆正确率,适合应用于信息处理和模式识别。

In order to improve the information processing capacity of chaotic neural networks,associative memory performance of a time-delay symmetric global coupled neural network was investigated by using a parameter modulated control method to control the coherent parameter.It can be observed that its output can be stabilized when only partial neurons enter the periodic orbits and the output sequence of the controlled network does not contain other patterns but the stored pattern corresponding to the initial input and its reverse pattern.The experimental results suggest that the network has good tolerance and excellent correct rate so that it is fit for information processing and pattern recognition.