文件名称:xiaoshijieshenjingwangluozhongdelianxiangjiyiyanji
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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.
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.
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小世界神经网络中的联想记忆研究.doc
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