Abstract
The macroscopic dynamics of an extremely diluted threestate neural network based on mutual information and mean-field theory arguments is studied in order to establish the stability of the stationary states. Results are presented in terms of the pattern-recognition overlap, the neural activity, and the activity-overlap. It is shown that the presence of synaptic noise is essential for the stability of states that recognize only the active patterns when the full structure of the patterns is not recognizable. Basins of attraction of considerable size are obtained in all cases for a not too large storage ratio of patterns. © Springer-VerlagBerlin Heidelberg2002.
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CITATION STYLE
Dominguez, D. R. C., Korutcheva, E., Theumann, W. K., & Erichsen, R. (2002). Flow diagrams of the quadratic neural network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2415 LNCS, pp. 129–134). Springer Verlag. https://doi.org/10.1007/3-540-46084-5_22
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