Numéro
J. Phys. I France
Volume 5, Numéro 1, January 1995
Page(s) 85 - 96
DOI https://doi.org/10.1051/jp1:1995116
DOI: 10.1051/jp1:1995116
J. Phys. I France 5 (1995) 85-96

The B.A.M. Storage Capacity

H. Englisch1, V. Mastropietro2 and B. Tirozzi3

1  Universität Leipzig, Inst. Für Informatik, D-04109 Leipzig, Germany
2  Dipartimento di Fisica, Università di Pisa, 56100 Pisa, Italia
3  Dipartimento di Matematica, Universita' di Roma "La Sapienza", 00185 Italia


(Received 22 February 1994, revised 23 September 1994, accepted 4 October 1994)

Abstract
The Bidirectional Associative Memory (B.A.M.) is a neural network which can store and associate pairs of data in the form of two patterns using an input network of M neurons and an output network with N neurons. Despite its interest there are no theoretical investigations about this model. We obtain the equations of state in a rigorous way using only the assumption that the Edwards-Anderson parameters associated to the two networks are self-averaging: this important property corresponds to the replica symmetry hypothesis in the replica calculations. A comparison between the methods used in the literature is made and the connection of our derivation with Peretto's method is shown. The storage capacity of the B.A.M. is computed when N=M and a bound on it is derived when $N\neq M$, in contrast with the strongly diluted case in which the critical capacity is unbounded for $N/M\to 0$ or $\to \infty$.



© Les Editions de Physique 1995

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.