Paper Info
Title
Recursive construction of periodic steady state for neural networks
Abstract
We present a strategy in order to build neural networks with long steady-state periodic behavior. This strategy allows us to obtain 2 n nonequivalent neural networks of size n , when the equivalence relation is the usual one in dynamical systems. As a particular case, we build a neural network with n neurons which realizes a cycle of period 2 n .
Year
DOI
Venue
1995
10.1016/0304-3975(94)00114-X
Theor. Comput. Sci.
Keywords
DocType
Volume
Recursive construction,neural network,periodic steady state
Journal
143
Issue
ISSN
Citations 
2
Theoretical Computer Science
3
PageRank 
References 
Authors
0.54
2
1
Name
Order
Citations
PageRank
Martín Matamala115821.63