Detalle de: Attractors in fully asymmetric neural networks
| Title | Attractors in fully asymmetric neural networks |
| Abstract |
The statistical properties of the length of the cycles and of the weights of the attraction basins in fully asymmetric neural networks (i.e. with completely uncorrelated synapses) are computed in the framework of the annealed approximation which we previously introduced for the study of Kauffman networks. Our results show that this model behaves essentially as a random map possessing a reversal symmetry. Comparison with numerical results suggests that the approximation could become exact in the large-size limit. |
| Apa Reference | Bastolla, U., & Parisi, G. (1997). Attractors in fully asymmetric neural networks. Journal of Physics A: Mathematical and General, 30(16), 5613–5631. 10.1088/0305-4470/30/16/007 |
| Doi | 10.1088/0305-4470/30/16/007 |
| Publication Date | 21 Aug 1997 |
| Publication Type | Article |
| Researcher | Ugo Bastolla |
| Ontology | Functional annotation, Function prediction, Structural bioinformatics, Molecular flexibility, Molecular evolution, Conservation Analysis, Evolutionary modelling, Ecological modelling, Sequence Alignment, Phylogenetic Analysis, Mutation Analysis and design, Network Biology, Structure-function relationship, Evolutionary rates, Microbial communities, Population dynamics |
| Research Groups | Computational biology and Bioinformatics (CBM): from Proteins to Ecosystems |
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