A flexible architecture for neural networks
J. Ouali, G. Saucier · 2003
A distributed, synchronous architecture for neural networks is presented. The basic processor is associated to one neuron and is able to autonomously perform all the steps of the learning and relaxation phases. Data circulation is implemented by shifting techniques. Customization of the network is done by fixing identification data in dedicated memory elements.>