In this paper, we present a neural network system related to about memory and recall that consists of one neuron group (the "cue ball") and a one-layer neural net (the "recall net"). This system realizes the bidirectional memorization learning between one cue neuron in the cue ball and the neurons in the recall net. It can memorize many patterns and recall these patterns or those that are similar at any time. Furthermore, the patterns are recalled at most the same time. This model's recall situation seems to resemble human recall of a variety of similar things almost simultaneously when one thing is recalled. It is also possible for additional learning to occur in the system without affecting the patterns memorized in advance. Moreover, the memory rate (the number of memorized patterns / the total number of neurons) is close to 100%; this system's rate is 0.987. Finally, pattern data constraints become an important aspect of this system.
翻译:在本文中, 我们展示了一个与记忆有关的神经网络系统, 并忆及由一个神经组( “ Cue ball ” ) 和一个层神经网( “ recall net ” ) 组成的神经网络系统。 这个系统可以实现球中一个提示性神经元和回溯性网中神经元之间的双向记忆学习。 它可以记住许多模式, 并记得这些模式或任何时刻类似的模式。 此外, 这些模式在最同时被回忆。 这个模式的回顾情况似乎类似于人类在回顾一件事情时几乎同时回忆各种类似的东西。 还可以在系统内进行更多的学习, 而不会影响预记忆模式。 此外, 记忆率( minorizized 模式数/神经元总数) 接近100%; 这个系统的比率是 0. 987. 最后, 模式数据限制成为这个系统的一个重要方面 。