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W339565228 abstract "Modelling of neural networks is still a very interesting and important field in the area of computing models. If input domains of neural networks are data structures represented by graphs and output domain is expected in a similar form, it is necessary to consider it in the process of neural network modelling. We propose four models of extended Self Organizing Maps (SOM) that can be applied to graph data structures as input and output domains together with learning algorithms. Extensions of the SOM model are based on the idea to remember information of connections in data structures (using some context neurons)." @default.
W339565228 created "2016-06-24" @default.
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W339565228 date "2015-01-01" @default.
W339565228 modified "2023-09-27" @default.
W339565228 title "Extended Self Organizing Maps for Structured Domain: Models and Learning" @default.
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W339565228 doi "https://doi.org/10.1007/978-3-319-10783-7_24" @default.
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