Sensitive Response of a Chaotic Wandering State to Memory Fragment Inputs in a Chaotic Neural Network Model
Sensitive Response of a Chaotic Wandering State to Memory Fragment Inputs in a Chaotic Neural Network Model
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DOI：
10.1142/s0218127404009867
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发表时间：
2004-04
期刊：
影响因子：
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通讯作者：
J. Kuroiwa;N. Masutani;S. Nara;K. Aihara
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文献类型：
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作者：
J. Kuroiwa;N. Masutani;S. Nara;K. Aihara
研究了一类混沌神经网络模型在混沌游荡状态下的动力学性质，讨论了该模型对记忆片段弱输入的敏感性。在一定的参数范围内，网络表现出弱的混沌游荡，这意味着网络动力学的轨道在状态空间中被定位在几个记忆模式周围。在其他参数区域，网络表现出高度发展的混沌游荡，即轨道通过所有记忆模式的废墟变得巡回。在后一种情况下，一旦由存储器片段组成的外部输入被施加到网络，轨道就在几个迭代步骤内快速移动到包括存储器片段的对应存储器模式的附近。因此，该模型中的混沌动力学是有效的记忆模式之间的瞬时搜索。
Dynamical properties of a chaotic neural network model in a chaotically wandering state are studied with respect to sensitivity to weak input of a memory fragment. In certain parameter regions, the network shows weakly chaotic wandering, which means that the orbits of network dynamics in the state space are localized around several memory patterns. In the other parameter regions, the network shows highly developed chaotic wandering, that is, the orbits become itinerant through ruins of all the memory patterns. In the latter case, once the external input consisting of a memory fragment is applied to the network, the orbit quickly moves to the vicinity of the corresponding memory pattern including the memory fragment within several iteration steps. Thus, chaotic dynamics in the model is effective for instantaneous search among memory patterns.