Implementation of a Kohonen map with learning capabilities
Vinesha Peiris, B. Hochet, Salah Abdo, Michel J. Declercq · 1991
An efficient and compact implementation of Kohonen neural networks with learning capability is described. Each synaptic weight is stored as a discrete voltage on a capacitor. The neurons compute the Manhattan distance between the input vector and their own synaptic vector using a dedicated arithmetics. The neighborhoods used during the learning phase are computed using a nonlinear resistor-based network.>