说明：  摘要： 本文研究了基于小世界结构的神经网络中的联想记忆模型。网络恢复存储模式的行为其实是无序参数为一有限值时的相位变化。越是规则的网络越是难以恢复记忆模式，且容易变成混合状态。另外，在无序参数的值适中时，对于一定数量的存储模式，最终得到恢复的效果可以达到最大。
(Abstract: This paper studies the structure based on small-world neural network model of associative memory. Network storage mode to restore the behavior is a disorder parameter for the limited value of the phase change. The more rules the more difficult to restore the network memory model, and easy to become a mixed state. In addition, the value of the parameter in the disordered medium, the model for a certain amount of storage, and ultimately be restored to achieve the greatest effect.)