用分维神经网络实现短期记忆
FRACTAL NEURAL NETWORKS FOR SHORT TERM MEMORY
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摘要: 神经网络中的突触连接矩阵储存有限的信息。当神经网络在线使用时,基于Hebb规则的网络模型将不再适用。本文提出用分维神经网络实现短期记忆,要求旧的模式随时间而遗忘,最近存储的模式可以可靠记忆。实验结果表明,该网络模型适用于在线工作,且优于对比方法。
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关键词:
- 分维神经网络; 短期记忆; 突触连接矩阵
Abstract: Synaptic connection matrix encodes limited information. It is well known that neural network memory with storage prescriptions based on Hebb s rule will collapse as more patterns are stored. By requiring that old patterns are automatically forgotten and the memory recalls only the most recent ones, a new short-term neural network memory based on Y.Baram s fractal neural network is proposed. Comparison is made with Morris and Wong's method and the experimental results are shown to be rather satisfactory and encouraging. -
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