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Spiking neural P systems with polarizations and astrocytes

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Abstract

Spiking neural P systems with polarizations (PSN P systems) use charges \((+,-,0)\) instead of regular expression to obtain excellent computation power and broad application prospect. In this work, astrocyte control mechanism is introduced into PSN P systems, spiking neural P systems with polarizations and astrocytes (PASN P systems) are constructed. Astrocytes are both excitatory and inhibitory influences on synapses, which can effectively reduce the consumption of computing resources (the use of fewer neurons). Because of the effects of astrocytes, PASN P systems are proved to have the computation power equivalent to Turing machines in generation and accepting modes. Furthermore, a small universal PASN P system with 82 neurons is given for computing any Turing computable function, that is, fewer neurons are used to construct the relatively simple and universal PASN P systems.

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References

  1. Păun, G., & Rozenberg, G. (2002). A guide to membrane computing. Theoretical Computer Science, 287(1), 73–100.

    Article  MathSciNet  MATH  Google Scholar 

  2. Păun, A., & Păun, G. (2007). Small universal spiking neural P systems. Biosystems, 90(1), 48–60.

    Article  MATH  Google Scholar 

  3. Păun, G. (2000). Computing with membranes. Journal of Computer and System Sciences, 61(1), 108–143.

    Article  MathSciNet  MATH  Google Scholar 

  4. Song, B., Li, K., Orellana-Martín, D., Pérez-Jiménez, M. J., & Pérez-Hurtado, I. (2021). A survey of nature-inspired computing: Membrane computing. ACM Computing Surveys (CSUR), 54(1), 1–31.

    Article  Google Scholar 

  5. Pan, L., Orellana-Martín, D., Song, B., & Pérez-Jiménez, M. J. (2020). Cell-like P systems with polarizations and minimal rules. Theoretical Computer Science, 816, 1–18.

    Article  MathSciNet  MATH  Google Scholar 

  6. Wu, T., Pan, L., Yu, Q., & Tan, K. C. (2020). Numerical spiking neural P systems. IEEE Transactions on Neural Networks and Learning Systems, 32(6), 2443–2457.

    Article  MathSciNet  Google Scholar 

  7. Wu, T., & Pan, L. (2020). The computation power of spiking neural P systems with polarizations adopting sequential mode induced by minimum spike number. Neurocomputing, 401, 392–404.

    Article  Google Scholar 

  8. Wu, T., & Jiang, S. (2021). Spiking neural P systems with a flat maximally parallel use of rules. Journal of Membrane Computing, 3(3), 221–231.

    Article  MathSciNet  MATH  Google Scholar 

  9. Ibarra, O. H., Păun, A., Păun, G., Rodríguez-Patón, A., Sosík, P., & Woodworth, S. (2007). Normal forms for spiking neural P systems. Theoretical Computer Science, 372(2–3), 196–217.

    Article  MathSciNet  MATH  Google Scholar 

  10. Pan, L., & Păun, G. (2010). Spiking neural P systems: An improved normal form. Theoretical Computer Science, 411(6), 906–918.

    Article  MathSciNet  MATH  Google Scholar 

  11. Ionescu, M., Păun, G., & Yokomori, T. (2006). Spiking neural P systems. Fundamenta Informaticae, 71(2–3), 279–308.

    MathSciNet  MATH  Google Scholar 

  12. Chen, H., Freund, R., Ionescu, M., Păun, G., & Pérez-Jiménez, M. J. (2007). On string languages generated by spiking neural P systems. Fundamenta Informaticae, 75(1–4), 141–162.

    MathSciNet  MATH  Google Scholar 

  13. Liu, X., & Ren, Q. (2021). Spiking neural membrane computing models. Processes, 9(5), 733.

    Article  Google Scholar 

  14. Cabarle, F. G. C., Adorna, H. N., Pérez-Jiménez, M. J., & Song, T. (2015). Spiking neural P systems with structural plasticity. Neural Computing and Applications, 26(8), 1905–1917.

    Article  MATH  Google Scholar 

  15. Peng, H., & Wang, J. (2018). Coupled neural P systems. IEEE Transactions on Neural Networks and Learning Systems, 30(6), 1672–1682.

    Article  MathSciNet  Google Scholar 

  16. Liu, Y., & Zhao, Y. (2022). Spiking neural P systems with membrane potentials, inhibitory rules, and anti-spikes. Entropy, 24(6), 834.

    Article  MathSciNet  Google Scholar 

  17. Wu, T., Zhang, L., Lyu, Q., & Jin, Y. (2022). Asynchronous spiking neural P systems with local synchronization of rules. Information Sciences, 588, 1–12.

    Article  Google Scholar 

  18. Jiang, S., Liu, Y., Xu, B., Sun, J., & Wang, Y. (2022). Asynchronous numerical spiking neural P systems. Information Sciences, 605, 1–14.

    Article  Google Scholar 

  19. Aman, B., & Ciobanu, G. (2022). The power of synchronizing rules in membrane computing. Information Sciences, 594, 360–370.

    Article  Google Scholar 

  20. Song, T., Pan, L., & Păun, G. (2014). Spiking neural P systems with rules on synapses. Theoretical Computer Science, 529, 82–95.

    Article  MathSciNet  MATH  Google Scholar 

  21. Zeng, X., Zhang, X., & Pan, L. (2009). Homogeneous spiking neural P systems. Fundamenta Informaticae, 97(1–2), 275–294.

    Article  MathSciNet  MATH  Google Scholar 

  22. de la Cruz, R. T. A., Cabarle, F. G. C., Macababayao, I. C. H., Adorna, H. N., & Zeng, X. (2021). Homogeneous spiking neural P systems with structural plasticity. Journal of Membrane Computing, 3(1), 10–21.

    Article  MathSciNet  MATH  Google Scholar 

  23. Zhang, X., Pan, L., & Păun, A. (2015). On the universality of axon P systems. IEEE Transactions on Neural Networks and Learning Systems, 26(11), 2816–2829.

    Article  MathSciNet  Google Scholar 

  24. Cabarle, F. G. C., Adorna, H. N., Jiang, M., & Zeng, X. (2017). Spiking neural P systems with scheduled synapses. IEEE Transactions on Nanobioscience, 16(8), 792–801.

    Article  Google Scholar 

  25. Song, T., Luo, L., He, J., Chen, Z., & Zhang, K. (2014). Solving subset sum problems by time-free spiking neural P systems. Applied Mathematics & Information Sciences, 8(1), 327.

    Article  Google Scholar 

  26. Ishdorj, T.-O., Leporati, A., Pan, L., Zeng, X., & Zhang, X. (2010). Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources. Theoretical Computer Science, 411(25), 2345–2358.

    Article  MathSciNet  MATH  Google Scholar 

  27. Noguchi, T., & Fujiwara, A. (2022). An asynchronous P system with a DPLL algorithm for solving SAT. International Journal of Networking and Computing, 12(2), 238–252.

    Article  Google Scholar 

  28. Song, B., & Zeng, X. (2021). Solving a PSPACE-complete problem by symport/antiport P systems with promoters and membrane division. Journal of Membrane Computing, 3(4), 296–302.

    Article  MathSciNet  MATH  Google Scholar 

  29. Henderson, A., Nicolescu, R., & Dinneen, M. J. (2020). Solving a PSPACE-complete problem with cP systems. Journal of Membrane Computing, 2(4), 311–322.

    Article  MathSciNet  MATH  Google Scholar 

  30. Aman, B., & Ciobanu, G. (2021). Travelling salesman problem in tissue p systems with costs. Journal of Membrane Computing, 3(2), 97–104.

    Article  MathSciNet  MATH  Google Scholar 

  31. Dong, J., Zhang, G., Luo, B., Yang, Q., Guo, D., Rong, H., Zhu, M., & Zhou, K. (2022). A distributed adaptive optimization spiking neural P system for approximately solving combinatorial optimization problems. Information Sciences, 596, 1–14.

    Article  Google Scholar 

  32. Tao, C., Yu, W., Wang, J., Peng, H., Chen, K., & Ming, J. (2016). Fault diagnosis of power systems based on triangular fuzzy spiking neural P systems. In International conference on bio-inspired computing: Theories and applications (pp. 385–398). Springer.

  33. Liu, Y., Chen, Y., Paul, P., Fan, S., Ma, X., & Zhang, G. (2021). A review of power system fault diagnosis with spiking neural P systems. Applied Sciences, 11(10), 4376.

    Article  Google Scholar 

  34. Peng, H., Wang, J., Pérez-Jiménez, M. J., Wang, H., Shao, J., & Wang, T. (2013). Fuzzy reasoning spiking neural P system for fault diagnosis. Information Sciences, 235, 106–116.

    Article  MathSciNet  MATH  Google Scholar 

  35. Lv, Z., Yang, Q., Peng, H., Song, X., & Wang, J. (2021). Computational power of sequential spiking neural P systems with multiple channels. Journal of Membrane Computing, 3(4), 270–283.

    Article  MathSciNet  MATH  Google Scholar 

  36. Valencia-Cabrera, L., & Song, B. (2020). Tissue P systems with promoter simulation with MeCoSim and P-Lingua framework. Journal of Membrane Computing, 2(2), 95–107.

    Article  MathSciNet  MATH  Google Scholar 

  37. Pérez-Hurtado, I., Orellana-Martín, D., Martínez-del-Amor, M. A., Valencia-Cabrera, L., & Riscos-Núñez, A. (2022). A new P-Lingua toolkit for agile development in membrane computing. Information Sciences, 587, 1–22.

    Article  Google Scholar 

  38. Buiu, C., Arsene, O., Cipu, C., & Patrascu, M. (2011). A software tool for modeling and simulation of numerical P systems. Biosystems, 103(3), 442–447.

    Article  Google Scholar 

  39. Siegelmann, H. T., & Sontag, E. D. (1992). On the computational power of neural nets. In: Proceedings of the fifth annual workshop on computational learning theory (pp. 440–449).

  40. Song, T., Jiang, Y., Shi, X., & Zeng, X. (2013). Small universal spiking neural P systems with anti-spikes. Journal of Computational and Theoretical Nanoscience, 10(4), 999–1006.

    Article  Google Scholar 

  41. Wu, T., Wang, Y., Jiang, S., & Shi, X. (2016). Small universal spiking neural P systems with homogenous neurons and synapses. Fundamenta Informaticae, 149(4), 451–470.

    Article  MathSciNet  MATH  Google Scholar 

  42. Kong, Y., Jiang, K., Chen, Z., & Xu, J. (2014). Small universal spiking neural p systems with astrocytes. Science and Technology, 17(1), 19–32.

    Google Scholar 

  43. Wu, T., Păun, A., Zhang, Z., & Pan, L. (2017). Spiking neural P systems with polarizations. IEEE Transactions on Neural Networks and Learning Systems, 29(8), 3349–3360.

    MathSciNet  Google Scholar 

  44. Jiang, S., Fan, J., Liu, Y., Wang, Y., & Xu, F. (2020). Spiking neural P systems with polarizations and rules on synapses. Complexity 2020.

  45. Volterra, A., & Meldolesi, J. (2005). Astrocytes, from brain glue to communication elements: The revolution continues. Nature Reviews Neuroscience, 6(8), 626–640.

    Article  Google Scholar 

  46. Păun, G. (2010). The Oxford Handbook of Membrane Computing. New York: Oxford University Press.

    Book  MATH  Google Scholar 

  47. Cavaliere, M., Ibarra, O. H., Păun, G., Egecioglu, O., Ionescu, M., & Woodworth, S. (2009). Asynchronous spiking neural P systems. Theoretical Computer Science, 410(24–25), 2352–2364.

    Article  MathSciNet  MATH  Google Scholar 

  48. Korec, I. (1996). Small universal register machines. Theoretical Computer Science, 168(2), 267–301.

    Article  MathSciNet  MATH  Google Scholar 

  49. Cireşan, D. C., Meier, U., Gambardella, L. M., & Schmidhuber, J. (2010). Deep, big, simple neural nets for handwritten digit recognition. Neural Computation, 22(12), 3207–3220.

    Article  Google Scholar 

  50. Trhan, P. (2010). The application of spiking neural networks in autonomous robot control. Computing and Informatics, 29(5), 823–847.

    MATH  Google Scholar 

  51. Khademian, F., Khanbabaie, R., & Babol, I. (2015). Practical applications of spiking neural network in information processing and learning. AcSIJ Advances in Computer Science: An International Journal, 4(4), 133–137.

    Google Scholar 

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

    Suxia Jiang, Zhichao Shen, Bowen Xu, Xiaoliang Zhu & Tao Liang

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  1. Suxia Jiang
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Jiang, S., Shen, Z., Xu, B. et al. Spiking neural P systems with polarizations and astrocytes. J Membr Comput 5, 55–68 (2023). https://doi.org/10.1007/s41965-023-00119-8

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