J. Phys. France
Volume 51, Numéro 17, septembre 1990
Page(s) 1797 - 1801
J. Phys. France 51, 1797-1801 (1990)
DOI: 10.1051/jphys:0199000510170179700

Pattern recognition in Hopfield type networks with a finite range of connections

Eva Koscielny-Bunde

Fachbereich Informatik, Universität Hamburg, D-2000 Hamburg 50, F.R.G.

We study pattern recognition in linear Hopfield type networks of N neurons where each neuron is connected to the z subsequent neurons such that the state of the ith neuron at time t + 1 is determined by the states of neurons i + 1, ...,i + z at time t. We find that for small values of z/N the retrieval behavior differs considerably from the behavior of diluted Hopfield networks. The maximum number of random patterns that can be retrieved increases in a non linear way with z and the asymptotic mean overlap between input and output patterns decreases sharply as z is decreased and reaches zero at a finite value of z.

8718S - Neural networks.
0705M - Neural networks, fuzzy logic, artificial intelligence.

Key words
neural nets -- pattern recognition