Programming a VG-RAM based Neural Network Computer

We propose a Virtual Generalizing Random Access Memory (VG-RAM) Weightless Neural Network (WNN) Computer (V\´Ger Computer for short). VG-RAM WNNs are very effective pattern recognition tools, offering fast training (one shot training) and competitive recognition performance, if compared with other current techniques. The V\´Ger Computer architecture was inspired on the organization of the human neocortex and is composed of hierarchically organized and recurrently interconnected layers of VG-RAM WNN neurons. One layer is connected to another in a way similar to cortico-cortical feed-forward and feedback connections between functionally adjacent and hierarchically organized areas. We have "programmed" the V\´Ger Computer for counting from 0 to 9 three times. Our preliminary experimental results showed that V\´Ger is capable of executing this sequence of actions in spite of strong interferences.