Hostname: page-component-6898cfcb55-zkb6p Total loading time: 0 Render date: 2026-11-11T18:33:57.537Z Has data issue: false hasContentIssue false
  • English
  • Français

The computational power of timed P systems with active membranes using promoters

Published online by Cambridge University Press:  09 August 2018

YUEGUO LUO,
HAIJUN TAN,
YING ZHANG and
YUN JIANG
YUEGUO LUO
Affiliation:
College of Computer Engineering, Yangtze Normal University, Chongqing 408100, China Email: ygluo@cqu.edu.cn, 21249892@qq.com, 77101258@qq.com
HAIJUN TAN
Affiliation:
College of Computer Engineering, Yangtze Normal University, Chongqing 408100, China Email: ygluo@cqu.edu.cn, 21249892@qq.com, 77101258@qq.com
YING ZHANG
Affiliation:
College of Computer Engineering, Yangtze Normal University, Chongqing 408100, China Email: ygluo@cqu.edu.cn, 21249892@qq.com, 77101258@qq.com
YUN JIANG
Affiliation:
School of Artificial Intelligence, Chongqing Technology and Business University, Chongqing 400067, China Email: 34976532@qq.com
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

P systems with active membranes are a class of bioinspired computing models, where the rules are used in the non-deterministic maximally parallel manner. In this paper, first, a new variant of timed P systems with active membranes is proposed, where the application of rules can be regulated by promoters with only two polarizations. Next, we prove that any Turing computable set of numbers can be generated by such a P system in the time-free way. Moreover, we construct a uniform solution to the $\mathcal{SAT}$ problem in the framework of such recognizer timed P systems in polynomial time, and the feasibility and effectiveness of the proposed system is demonstrated by an instance. Compared with the existing methods, the P systems constructed in our work require fewer necessary resources and RS-steps, which show that the solution is effective to NP-complete problem.

Information

Type
Paper
Information
Mathematical Structures in Computer Science , Volume 29 , Issue 5 , May 2019, pp. 663 - 680
Copyright
Copyright © Cambridge University Press 2018 

References

Alhazov, A., Pan, L. and Păun, G. (2004). Trading polarizations for labels in P systems with active membranes. Acta Informatica 41 (2-3) 111–144.Google Scholar
Bottoni, P., Martín-Vide, C. and Păun, G. (2002). Membrane systems with promoters/inhibitors. Acta Informatica 38 (10) 695–720.Google Scholar
Cavaliere, M. and Sburlan, D. (2005). Time-Independent P Systems. Lecture Notes in Computer Science 3365, Springer-Verlag, Berlin 239–258.Google Scholar
Gheorghe, M., Păun, G. and Pérez-Jiménez, M.J. (2013). Research frontiers of membrane computing: Open problems and research topics. International Journal of Foundations of Computer Science 24 (5) 547–623.Google Scholar
Guo, P., Ji, J. and Chen, H. (2015). Solving all-SAT problems by P systems. Chinese Journal of Electronics 24 (4) 744–749.Google Scholar
Gutiérrez-Naranjo, M.A., Pérez-Jiménez, M.J. and Romero-Campero, F.J. (2007). A uniform solution to SAT using membrane creation. Theoretical Computer Science 371 (1-2) 54–61.Google Scholar
Ionescu, M., Păun, G. and Yokomori, T. (2006). Spiking neural P systems. Fundamenta Informaticae 71 (2) 279–308.Google Scholar
Leporati, A., Mauri, G., Zandron, C., Păun, G. and Pérez-Jiménez, M. J. (2009). Uniform solutions to SAT and subset sum by spiking neural P systems. Natural Computing 8 (4) 681–702.Google Scholar
Luo, Y., Xiong, Z., Tan, H. and Xia, S. (2015). A uniform algorithm of solving all-SAT using membrane systems. Journal of Computational & Theoretical Nanoscience 12 (12) 5825–5832.Google Scholar
Luo, Y., Xiong, Z., Chen, Y. and Tan, H. (2016). Efficient solutions to all-SAT by P systems with active membranes. Journal of Computational & Theoretical Nanoscience 13 (6) 3887–3894.Google Scholar
Minsky, M. (1967). Computation: Finite and Infinite Machines, Prentice-Hall Inc.Google Scholar
Pan, L., Zeng, X. and Zhang, X. (2011). Time-free spiking neural P systems. Neural Computation 23 (5) 1320–1342.Google Scholar
Pan, L. and Pérez-Jiménez, M.J. (2010). Computational complexity of tissue-like P systems. Journal of Complexity 26 (3) 296–315.Google Scholar
Pan, L., Wang, Y.S., Jiang, S. and Song, B. (2017). Flat maximal parallelism in tissue P systems with promoters. Romanian Journal of Information Science and Technology 20 (1) 42–56.Google Scholar
Păun, A. and Păun, G. (2002). The power of communication: P systems with symport/antiport. New Generation Computing 20 (3) 295–305.Google Scholar
Păun, A. and Păun, G. (2007). Small universal spiking neural P systems. Biosystems 90 (1) 48–60.Google Scholar
Păun, G. (1999a). Introduction to membrane computing. Theoretical Computer Science 287 (1) 73–100.Google Scholar
Păun, G. (1999b). P systems with active membranes: Attacking NP complete problems. Journal of Automata Languages & Combinatorics 6 (1) 75–90.Google Scholar
Păun, G. (2000). Computing with membranes. Journal of Computer and System Sciences 61 (1) 108–143.Google Scholar
Păun, G., Pérez-Jiménez, M.J. and Riscos, A. (2008). Tissue P systems with cell division. International Journal of Computers Communications & Control 3 (3) 295–303.Google Scholar
Păun, G., Suzuki, Y., Tanaka, H. and Yokomori, T. (2004). On the power of membrane division in P systems. Theoretical Computer Science 324 (1) 61–85.Google Scholar
Pérez-Jiménez, M.J. and Sosik, P. (2015). An optimal frontier of the efficiency of tissue P systems with cell separation. Fundamenta Informaticae 138 (1-2) 45–60.Google Scholar
Song, B. and Pan, L. (2015a). Computational efficiency and universality of timed P systems with active membranes. Theoretical Computer Science 567, 74–86.Google Scholar
Song, B., Song, T. and Pan, L. (2015b). Time-free solution to SAT problem by P systems with active membranes and standard cell division rules. Natural Computing 14 (4) 673–681.Google Scholar
Song, B., Pérez-Jiménez, M.J. and Pan, L. (2015c). Efficient solutions to hard computational problems by P systems with symport/antiport rules and membrane division. BioSystems 130, 51–58.Google Scholar
Song, B., Zhang, C. and Pan, L. (2016a). Tissue-like P systems with evolutional symport/antiport rules. Information Sciences 378, 177–193.Google Scholar
Song, B., Pérez-Jiménez, M.J. and Pan, L. (2016b). An efficient time-free solution to SAT problem by P systems with proteins on membranes. Journal of Computer and System Sciences 82 (6) 1090–1099.Google Scholar
Song, B., Pérez-Jiménez, M.J. and Pan, L. (2017a). An efficient time-free solution to QSAT problem using P systems with proteins on membranes. Information and Computation 256C, 287–299.Google Scholar
Song, B., Song, T. and Pan, L. (2017b). A time-free uniform solution to subset sum problem by tissue P systems with cell division. Mathematical Structures in Computer Science 27, 17–32.Google Scholar
Song, B., Pérez-Jiménez, M.J., Păun, G. and Pan, L. (2016c). Tissue P systems with channel states working in the flat maximally parallel way. IEEE Transactions on NanoBioscience 15 (7) 645–656.Google Scholar
Song, T., Macias-Ramos, L. and Pan, L. (2014). Time-free solution to SAT problem using P systems with active membranes. Theoretical Computer Science 529, 61–68.Google Scholar
Song, T. and Pan, L. (2016). Spiking neural P systems with request rules. Neurocomputing 193, 193–200.Google Scholar
Wu, T., Zhang, Z. and Pan, L. (2016). On languages generated by cell-like spiking neural P systems. IEEE Transactions on Nanobioscience 15 (5) 455–467.Google Scholar
Zeng, X., Xu, L., Liu, X. and Pan, L. (2014a). On languages generated by spiking neural P systems with weights. Information Sciences 278 (10) 423–433.Google Scholar
Zeng, X., Pan, L. and Pérez-Jiménez, M.J. (2014b). Small universal simple spiking neural P systems with weights. Science China 57 (9) 1–11.Google Scholar
Zhang, G., Gheorghe, M. and Li, Y. (2012). A membrane algorithm with quantum-inspired subalgorithms and its application to image processing. Natural Computing 11 (4) 701–717.Google Scholar
Zhang, G., Gheorghe, M., Pan, L. and Pérez-Jiménez, M.J. (2014). Evolutionary membrane computing: A comprehensive survey and new results. Information Sciences 279) 528–551.Google Scholar
Zhang, X., Liu, Y., Luo, B. and Pan, L. (2014). Computational power of tissue P systems for generating control languages. Information Sciences 278 (10) 285–297.Google Scholar
Zhang, X., Pan, L. and Păun, A. (2017). On the universality of axon P systems. IEEE Transactions on Neural Networks & Learning Systems 26 (11) 2816–2829.Google Scholar