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- W2897747106 abstract "The effect of different interconnecting topologies on the performance of SOM networks is investigated. Three different databases (digits, musical symbols and letters dataset) are considered, and small world, correlated models, and the deactivation network topologies were taken into account. We show that the topology has a definite influence on the performance of the network at short and middle learning time scales. The addition of long-range connections in the deactivation model tended to reduce accuracy. In addition, we examined the effect of degree-degree correlations, or assortativity, on SOM neural networks. It has been shown that high assortativity values tend to decrease the classification error." @default.
- W2897747106 created "2018-10-26" @default.
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- W2897747106 date "2018-07-01" @default.
- W2897747106 modified "2023-09-24" @default.
- W2897747106 title "The impact of Interconnecting Topologies on SOM Neural Networks" @default.
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- W2897747106 doi "https://doi.org/10.1109/ijcnn.2018.8489044" @default.
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