On the capacity of multilayer neural networks trained with backpropagation.
The capacity of a layered neural network for learning hetero-associations is studied numerically as a function of the number M of hidden neurons. We find that there is a sharp change in the learning ability of the network as the number of hetero-associations increases. This fact allows us to define a maximum capacity C for a given architecture. It is found that C grows logarithmically with M.
Miranda
E N
EN
CRICYT - CONICET, Mendoza, Argentina. emiranda@lab.cricyt.edu.ar
D008433:Mathematics; D008962:Models, Theoretical; D016571:Neural Networks, Computer