  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.
