Digital neural network system based in new concepts on the recall phase dynamics

In this paper we present an electronic system designed to emulate neural networks. Two major restrictions are assumed: discrete synapses (+1,0,−1) and threshold-type neurons. Drawbacks given by restrictions are solved with a more complex learning algorithm that maps real valued configurations for synapses into bipolar ones. The central unit of the system is an ASIC designed in accordance with a new sequential dynamics, which is faster and with better recall characteristics. As a result, the system designed has a fast recall phase and a large number of neurons. A handwritten OCR system is being designed.