Abstract
Fuzzy Reasoning Spiking Neural P systems (FRSN P systems, for short) is a variant of Spiking Neural P systems incorporating fuzzy logic elements that make it suitable to model fuzzy diagnosis knowledge and reasoning required for fault diagnosis applications. In this sense, several FRSN P system variants have been proposed, dealing with real numbers, trapezoidal numbers, weights, etc. The model incorporating real numbers was the first introduced [13], presenting promising applications in the field of fault diagnosis of electrical systems. For this variant, a matrix-based algorithm was provided which, when executed on parallel computing platforms, fully exploits the model maximally parallel capacities. In this paper we introduce a P-Lingua framework extension to parse and simulate FRSN P systems with real numbers. Two simulators, implementing a variant of the original matrix-based simulation algorithm, are provided: a sequential one (written in Java), intended to run on traditional CPUs, and a parallel one, intended to run on CUDA-enabled devices.
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Acknowledgements
This work was supported by Project TIN2012-37434 of the Ministerio de Economía y Competitividad of Spain, cofinanced by FEDER funds. The authors also acknowledge the support of the GPU Research Center program granted by NVIDIA to the University of Seville.
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Macías-Ramos, L.F., Martínez-del-Amor, M.A., Pérez-Jiménez, M.J. (2015). Simulating FRSN P Systems with Real Numbers in P-Lingua on sequential and CUDA platforms. In: Rozenberg, G., Salomaa, A., Sempere, J., Zandron, C. (eds) Membrane Computing. CMC 2015. Lecture Notes in Computer Science(), vol 9504. Springer, Cham. https://doi.org/10.1007/978-3-319-28475-0_18
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DOI: https://doi.org/10.1007/978-3-319-28475-0_18
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