Abstract
By making use of quantum parallelism, quantum processes provide parallel modelling for fuzzy connectives and the corresponding computations of quantum states can be simultaneously performed, based on the superposition of membership degrees of an element with respect to the different fuzzy sets. Such description and modelling is mainly focussed on representable fuzzy Xor connectives and their dual constructions. So, via quantum computing not only the interpretation based on traditional quantum circuit is considered, but also the notion of quantum process in the qGM model is applied, proving an evaluation of a corresponding simulation by considering graphical interfaces of the VPE-qGM programming environment. The quantum interpretations come from measurement operations performed on the corresponding quantum states.
This work is supported by the Brazilian funding agencies CNPq (Ed. Universal and PQ, under the process numbers 448766/2014-0 and 309533/2013-9) and FAPERGS (Ed. 02/2014 - PqG, under the process number 11/1520-1).
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Ávila, A., Schmalfuss, M., Reiser, R., Kreinovich, V. (2015). Fuzzy Xor Classes from Quantum Computing. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9120. Springer, Cham. https://doi.org/10.1007/978-3-319-19369-4_28
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DOI: https://doi.org/10.1007/978-3-319-19369-4_28
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