A cortronic neural network defines connections between neurons in a number of regions (0, 1, ..., N-1) using target lists, which identify the output connections of each neuron and the connection strength. Neurons are preferably sparsely interconnected between regions (0, 1, ..., N-1). Training of connection weights employs a three stage process, which involves computation of the contribution to the input intensity of each neuron by every currently active neuron, a competition process that determines the next set of active neurons based on their current input intensity, and a weight adjustment process that updates and normalizes the connection weights based on which neurons won the competition process, and their connectivity with other winning neurons.
CORTRONIC NEURAL NETWORKS WITH DISTRIBUTED PROCESSING