P. Andriani
Innovation systems by nonlinear networks
Andriani, P.; Conti, F.; Fortuna, L.; Frasca, M.; Passiante, G.; Rizzo, A.
Authors
F. Conti
L. Fortuna
M. Frasca
G. Passiante
A. Rizzo
Abstract
Cellular Neural Networks (CNNs) constitute a powerful paradigm for modeling complex systems. Innovation systems are complex systems in which small and medium enterprises play the role of simple units interacting with each other. In this paper, innovation systems based on CNN are investigated. It is shown how a model based on CNN can reproduce the main features of innovation systems and how this model can be generalized to include different aspects of the actors of the financial market.
Citation
Andriani, P., Conti, F., Fortuna, L., Frasca, M., Passiante, G., & Rizzo, A. (2006). Innovation systems by nonlinear networks. Nonlinear Dynamics, 44(1-4), 263-268. https://doi.org/10.1007/s11071-006-1999-0
Journal Article Type | Article |
---|---|
Publication Date | Jun 1, 2006 |
Deposit Date | Mar 24, 2010 |
Journal | Nonlinear Dynamics |
Print ISSN | 0924-090X |
Electronic ISSN | 1573-269X |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Volume | 44 |
Issue | 1-4 |
Pages | 263-268 |
DOI | https://doi.org/10.1007/s11071-006-1999-0 |
Keywords | Connectivity level, Cellular Neural Networks, Innovation diffusion. |
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