Izhikevich神经元网络的同步与联想记忆

联想记忆是人脑的一项重要功能。以Izhikevich神经元模型为节点，构建神经网络，神经元之间采用全连结的方式；以神经元群体的时空编码（spatio-temporal coding）理论研究所构建神经网络的联想记忆功能。在加入高斯白噪声的情况下，调节网络中神经元之间的连接强度的大小，当连接强度和噪声强度达到一个阈值时网络中部分神经元同步放电，实现了存储模式的联想记忆与恢复。仿真结果表明，神经元之间的连接强度在联想记忆的过程中发挥了重要的作用，噪声可以促使神经元间的同步放电，有助于神经网络实现存储模式的联想记忆与恢复。

THE SYNCHRONIZATION AND ASSOCIATIVE MEMORY OF IZHIKEVICH NEURAL NETWORK

Associative memory is a basic function of human brain. A neural network composed of Izhikevich neuron model is presented in this paper. All the neurons in the network are connected to each other. The associative memory of neural system is studied with the spatio-temporl theory. When there is Gaussian white noise present in the input signal of the neural network, through the adjusting of the connection weight, parts of the neurons fire synchronously, the associative memory and retrieval of the stored memory pattern is achieved. The simulation results show that noise can promotes the synchrony of the firing and is helpful for the associative memory and retrieval of the stored memory. The connection weight plays an important role in the associative memory of the stored memory pattern.