In this work, we propose the study of SN P systems as classical information encoders. By taking the spike train of an SN P system as a (binary) source of information, we can obtain different languages according to a previously defined encoding alphabet. We provide a characterization of the language families generated by the SN P systems in this way. This characterization depends on the way we define the encoding scheme: bounded or not bounded and, in the first case, with one-to-one or non injective encodings. Finally, we propose a network topology in order to define a cascading encoder.
CITATION STYLE
Sempere, J. M. (2018). Families of languages encoded by SN P systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10725 LNCS, pp. 262–269). Springer Verlag. https://doi.org/10.1007/978-3-319-73359-3_17
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