Abstract
In this paper a recurrent network, which consists of O(√m log m) RBF (radial basis functions)units with maximum norm employing any activation function that has different values in at least two nonnegative points, is constructed so as to implement a given deterministic finite automaton with m states the underlying simulation proves to be robust with respect to analog noise for a large class of smooth activation functions with a special type of inflexion.
Research supported by GA AS CR Grant B2030007.
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Šorel, M., Šíma, J. (2000). Robust Implementation of Finite Automata by Recurrent RBF Networks. In: Hlaváč, V., Jeffery, K.G., Wiedermann, J. (eds) SOFSEM 2000: Theory and Practice of Informatics. SOFSEM 2000. Lecture Notes in Computer Science, vol 1963. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44411-4_32
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DOI: https://doi.org/10.1007/3-540-44411-4_32
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