Title
Dynamical properties of min-max networks.
Abstract
In this paper we study the dynamical behavior of a class of neural networks where the local transition rules are max or min functions. We prove that sequential updates define dynamics which reach the equilibrium in O(n2) steps, where n is the size of the network. For synchronous updates the equilibrium is reached in O(n) steps. It is shown that the number of fixed points of the sequential update is at most n. Moreover, given a set of p < or = n vectors, we show how to build a network of size n such that all these vectors are fixed points.
Year
DOI
Venue
2000
10.1142/S0129065700000387
International journal of neural systems
Field
DocType
Volume
Algorithm,Fixed point,Artificial neural network,Mathematics
Journal
10
Issue
ISSN
Citations 
6
0129-0657
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
E. Goles118127.13
Martín Matamala215821.63
Pablo A. Estévez300.68