Abstract
SN P systems with multiple channels are a new variant of spiking neural P systems (SN P systems, in short), which introduce channel labels into spiking rules. The computational power of SN P systems with multiple channels in computing Turing computable function is investigated, and two small SN P systems with multiple channels are constructed in this work. We obtain two universal systems with 57 neurons using standard spiking rules and 39 neurons using extended spiking rules, respectively.
Supported by the Chunhui Project Foundation of the Education Department of China (Nos. Z2017082, Z2016143 and Z2016148), Foundation of Sichuan Province Key Laboratory of Power Electronics Energy-saving Technologies & Equipment (No. szjj2015-065), National Natural Science Foundation of China (Nos. 61472328 and 61703345), Sichuan Province Key Laboratory of Power Electronics Energy-saving Technologies & Equipment (No. szjj2016-048) and Research Foundation of the Education Department of Sichuan province (No. 17TD0034), China.
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References
Pǎun, G.: Computing with membranes. J. Comput. Syst. Sci. 61(1), 108–143 (2000)
Pǎun, G.: Membrane Computing: An Introduction. Springer, Berlin (2002). https://doi.org/10.1007/978-3-642-56196-2
Martín-Vide C., Pǎun G., Pazos J., Rodríguez-Patón A.: Tissue P systems. Theor. Comput. Sci. 296, 295–326 (2003)
Pǎun, G., Rozenberg, G., Salomaa, A.: The Oxford Handbook of Membrane Computing. Oxford University Press, Oxford (2010)
Ionescu, M., Pǎun, G., Yokomori, T.: Spiking neural P systems. Fundam. Informaticae 71, 279–309 (2006)
Pǎun, A., Pǎun, G.: Small universal spiking neural P systems. BioSystems 90(1), 48–60 (2007)
Neary, T.: A universal spiking neural P system with 11 neurons. In: Proceedings of the Eleventh International Conference on Membrane Computing, pp. 327–346. Springer, Jena (2010)
Neary, T.: Three small universal spiking neural P systems. Theor. Comput. Sci. 567, 2–20 (2008)
Zhang, X., Zeng, X., Pan, L.: Smaller universal spiking neural P systems. Fundam. Informaticae 87(1), 117–136 (2008)
Neary, T.: A boundary between universality and non-universality in extended spiking neural P systems. In: Dediu, A.-H., Fernau, H., Martín-Vide, C. (eds.) LATA 2010. LNCS, vol. 6031, pp. 475–487. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13089-2_40
Chen, H., Freund, R., Ionescu, M., Pǎun, G., Pérez-Jiménez, M.: On string languages generated by spiking neural P systems. Fundam. Informaticae 75(1), 141–162 (2007)
Pǎun, G., Pérez-Jiménez, M., Rozenberg, G.: Spike trains in spiking neural P systems. Int. J. Found. Comput. Sci. 17(4), 975–1002 (2006)
Wang, J., Hoogeboom, H.J., Pan, L., Pǎun, G., Pérez-Jiménez, M.J.: Spiking neural P systems with weights. Neural Comput. 22(10), 2615–2646 (2010)
Zeng, X., Zhang, X., Song, T., Pan, L.: Spiking neural P systems with thresholds. Neural Comput. 26(7), 1340–1361 (2014)
Pan, L., Zeng, X., Zhang, X., Jiang, Y.: Spiking neural P systems with weighted synapses. Neural Process. Lett. 35(1), 13–27 (2012)
Zeng, X., Pan, L., Pérez-Jiménez, M.J.: Small universal simple spiking neural P systems with weights. Sci. China Inf. Sci. 57(9), 1–11 (2014)
Zhang, X., Zeng, X., Pan, L.: Weighted spiking neural P systems with rules on synapses. Fundam. Informaticae 134(1–2), 201–218 (2014)
Zeng, X., Xu, L., Liu, X., Pan, L.: On languages generated by spiking neural P systems with weights. Inf. Sci. 278(10), 423–433 (2014)
Song, T., Pan, L., Pǎun, G.: Spiking neural P systems with rules on synapses. Theor. Comput. Sci. 529(4), 82–95 (2014)
Song, T., Xu, J., Pan, L.: On the universality and non-universality of spiking neural P systems with rules on synapses. IEEE Trans. Nanobiosci. 14(8), 960–966 (2015)
Song, T., Pan, L.: Spiking neural P systems with rules on synapses working in maximum spiking strategy. Theor. Comput. Sci. 14(1), 38–44 (2015)
Pan, L., Pǎun, G.: Spiking neural P systems with anti-spikes. Int. J. Comput. Commun. Control IV(3), 273–282 (2009)
Krithivasan, K., Metta, V.P., Garg, D.: On string languages generated by spiking neural P systems with anti-spikes. Int. J. Found. Comput. Sci. 22(1), 15–27 (2011)
Pan, L., Wang, J., Hoogeboom, H.J.: Spiking neural P systems with astrocytes. Neural Comput. 24(3), 805–825 (2014)
Song, T., Gong, F., Liu, X., Zhao, Y., Zhang, X.: Spiking neural P systems with white hole neurons. IEEE Trans. Nanobiosci. 15(7), 666–673 (2016)
Zhang, X., Pan, L., Pǎun, A.: On the universality of axon P systems. IEEE Trans. Neural Netw. Learn. Syst. 26(11), 2816–2829 (2015)
Zeng, X., Zhang, X., Pan, L.: Homogeneous spiking neural P systems. Fundam. Informaticae 97(1), 275–294 (2009)
Song, T., Wang, X., Zhang, Z., Chen, Z.: Homogeneous spiking neural P systems with anti-spikes. Neural Comput. Appl. 24(7–8), 1833–1841 (2014)
Jiang, K., Chen, W., Zhang, Y., Pan, L.: Spiking neural P systems with homogeneous neurons and synapses. Neurocomputing 171(C), 1548–1555 (2015)
Song, T., Zheng, P., Wong, M.L.D., Wang, X.: Design of logic gates using spiking neural P systems with homogeneous neurons and astrocytes-like control. Inf. Sci. 372, 380–391 (2016)
Ibarra, O.H., Pǎun, A., Rodríguez-Patón, A.: Sequential SNP systems based on min/max spike number. Theor. Comput. Sci. 410(30), 2982–2991 (2009)
Song, T., Pan, L., Jiang, K., Song, B., Chen, W.: Normal forms for some classes of sequential spiking neural P systems. IEEE Trans. NanoBiosci. 12(3), 255–264 (2013)
Zhang, X., Zeng, X., Luo, B., Pan, L.: On some classes of sequential spiking neural P systems. Neural Comput. 26(5), 974–997 (2014)
Zhang, X., Luo, B., Fang, X., Pan, L.: Sequential spiking neural P systems with exhaustive use of rules. BioSystems 108(1–3), 52–62 (2012)
Cavaliere, M., Ibarra, O.H., Pǎun, G., Egecioglu, O., Ionescu, M., Woodworth, S.: Asynchronous spiking neural P systems. Theor. Comput. Sci. 410(24), 2352–2364 (2009)
Song, T., Pan, L., Pǎun, G.: Asynchronous spiking neural P systems with local synchronization. Inf. Sci. 219(24), 197–207 (2013)
Song, T., Zou, Q., Liu, X., Zeng, X.: Asynchronous spiking neural P systems with rules on synapses. Neurocomputing 151(3), 1439–1445 (2015)
Peng, H., Wang, J., Pérez-Jiménez, M.J., Wang, H., Shao, J., Wang, T.: Fuzzy reasoning spiking neural P system for fault diagnosis. Inf. Sci. 235(6), 106–116 (2013)
Wang, J., Peng, H.: Adaptive fuzzy spiking neural P systems for fuzzy inference and learning. Int. J. Comput. Math. 90(4), 857–868 (2013)
Wang, T., Zhang, G., Zhao, J., He, Z., Wang, J., Pérez-Jiménez, M.J.: Fault diagnosis of electric power systems based on fuzzy reasoning spiking neural P systems. IEEE Trans. Power Syst. 30(3), 1182–1194 (2015)
Tu, M., Wang, J., Peng, H., Shi, P.: Application of adaptive fuzzy spiking neural P systems in fault diagnosis of power systems. Chin. J. Electron. 23(1), 87–92 (2014)
Wang, T., Zhang, G., Pérez-Jiménez, M.J., Cheng, J.: Weighted fuzzy reasoning spiking neural P systems: application to fault diagnosis in traction power supply systems of high-speed railways. J. Comput. Theor. Nanosci. 12(7), 1103–1114 (2015)
Wang, J., Shi, P., Peng, H., Pérez-Jiménez, M.J., Wang, T.: Weighted fuzzy spiking neural P systems. IEEE Trans. Fuzzy Syst. 21(2), 209–220 (2013)
Wang, T., Zhang, G., Pérez-Jiménez, M.J.: Fuzzy membrane computing: theory and applications. Int. J. Comput. Commun. Control 10(6), 904–935 (2015)
Díaz-Pernil, D., Peńa-Cantillana, F., Gutiérrez-Naranjo, M.A.: A parallel algorithm for skeletonizing images by using spiking neural P systems. Neurocomputing 115, 81–91 (2013)
Zhang, G., Rong, H., Neri, F., Pérez-Jiménez, M.J.: An optimization spiking neural P system for approximately solving combinatorial optimization problems. Int. J. Neural Syst. 24(5), 1440006 (2014)
Ishdorj, T.O., Leporati, A., Pan, L., Zeng, X., Zhang, X.: Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources. Theor. Comput. Sci. 411(25), 2345–2358 (2010)
Leporati, A., Mauri, G., Zandron, C., Pǎun, G., Pérez-Jiménez, M.J.: Uniform solutions to SAT and Subset Sum by spiking neural P systems. Nat. Comput. 8(4), 681–702 (2009)
Pan, L., Pǎun, G., Pérez-Jiménez, M.J.: Spiking neural P systems with neuron division and budding. Sci. China Inf. Sci. 54(8), 1596–1607 (2011)
Peng, H., Yang, J., Wang, J., Wang, T., Sun, Z., Song, X., Lou, X., Huang, X.: Spiking neural P systems with multiple channels. Neural Netw. 95, 66–71 (2017)
Rozenberg, G., Salomaa, A.: Handbook of Formal Languages. Springer, Berlin (1997). https://doi.org/10.1007/978-3-642-59136-5
Korec, I.: Small universal register machines. Theor. Comput. Sci. 168(2), 267–301 (1996)
Wu, T., Zhang, Z., Pǎun, G., Pan, L.: Cell-like spiking neural P systems. Theor. Comput. Sci. 623(11), 180–189 (2016)
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Song, X. et al. (2019). On Small Universality of Spiking Neural P Systems with Multiple Channels. In: Hinze, T., Rozenberg, G., Salomaa, A., Zandron, C. (eds) Membrane Computing. CMC 2018. Lecture Notes in Computer Science(), vol 11399. Springer, Cham. https://doi.org/10.1007/978-3-030-12797-8_16
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