Abstract
In this paper a new neural network structure, called Syntactical Self-Organizing Map (SSOM), is introduced. SSOM is obtained from classical (numerical) Kohonen neural network and is specifically for classifying the syntactical structures, like: strings, trees or graphs. After defining the SSOM structure and algorithm, in the third part of the paper an application of character recognition is solved using SSOM. To point out the performances of the new neural network, a comparison of results obtained using the SSOM and the Fu and Lu's clustering algorithm [10] for the same application is done. Moreover, we show that the syntactical Kohonen map have also the topological feature like the numerical one.
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© 1997 Springer-Verlag Berlin Heidelberg
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Grigore, O. (1997). Syntactical Self-Organizing Map. In: Reusch, B. (eds) Computational Intelligence Theory and Applications. Fuzzy Days 1997. Lecture Notes in Computer Science, vol 1226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62868-1_103
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DOI: https://doi.org/10.1007/3-540-62868-1_103
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