Title
Necessary and sufficient condition for multistability of neural networks evolving on a closed hypercube.
Abstract
The paper considers nonsmooth neural networks described by a class of differential inclusions termed differential variational inequalities (DVIs). The DVIs include the relevant class of neural networks, introduced by Li, Michel and Porod, described by linear systems evolving in a closed hypercube of Rn. The main result in the paper is a necessary and sufficient condition for multistability of DVIs with nonsymmetric and cooperative (nonnegative) interconnections between neurons. The condition is easily checkable and provides a sharp bound between DVIs that can store multiple patterns, as asymptotically stable equilibria, and those for which this is not possible. Numerical examples and simulations are presented to confirm and illustrate the theoretic findings.
Year
DOI
Venue
2014
10.1016/j.neunet.2014.02.010
Neural Networks
Keywords
Field
DocType
Neural networks,Multistability,Differential variational inequalities,Cooperative dynamical systems,Nonsmooth dynamical systems
Differential inclusion,Mathematical optimization,Linear system,Multistability,Artificial neural network,Hypercube,Mathematics,Variational inequality,Stability theory
Journal
Volume
Issue
ISSN
54
1
0893-6080
Citations 
PageRank 
References 
5
0.45
27
Authors
4
Name
Order
Citations
PageRank
Mauro Di Marco120518.38
Mauro Forti239836.80
Massimo Grazzini313111.01
Luca Pancioni420717.58