Self-association in multilayer linear networks with limited connectivity.
We study the behavior of linear neural networks having constrained connectivity of Hebbian and anti-Hebbian synapses. We derive some general results for cascade architectures and a formula for the number of layers necessary to obtain a sufficiently close approximation to the principal components at the final outputs. Results of a number of simulations confirm the analyses.
Palmieri
Francesco
F
Dipartimento di Ingegneria Elettronica, Università degli Studi di Napoli 'Federico II', Napoli, Italy
Corvino
Michele
M